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Helicobacter pylori (H. pylori) infection is a known cause of many digestive diseases, including gastritis, peptic ulcers, and gastric cancer. However, the underlying mechanisms by which H. pylori infection triggers these disorders are still not clearly understood. Gastric cancer is a slow progressing disease, which makes it difficult to study. We have developed an accelerated disease progression mouse model, which leverages mice deficient in the myeloid differentiation primary response 88 gene (Myd88-/-) infected with Helicobacter felis (H. felis). Using this model and gastric biopsy samples from patients, we report that activation of the Toll/interleukin-1 receptor (TIR)-domain-containing adaptor inducing interferon-β (TRIF)-type I interferon (IFN-I) signaling pathway promotes Helicobacter-induced disease progression toward severe gastric pathology and gastric cancer development. Further, results implicated downstream targets of this pathway in disease pathogenesis. These findings may facilitate stratification of Helicobacter-infected patients and thus enable treatment prioritization of patients.

Objectives: Ascites, often associated with critical pathologies such as liver cirrhosis or bowel perforation, can be complicated by fungal infection, increasing mortality especially in intensive care settings and demanding rapid diagnosis and adequate treatment. Traditional microbiological diagnostic methods have limited sensitivity in accurately identifying fungal pathogens in ascitic fluid. Alternative diagnostic methods may offer important insights to enable guiding of antifungal therapy and refining empirical treatment strategies. The objective of this study was to evaluate the potential of next-generation sequencing methods to identify specific fungal pathogens responsible for ascitic fluid infections. Methods: We prospectively collected 50 ascitic fluid samples from ICU patients with suspected ascites infection. In addition to standard culture-based microbiological testing, an ascitic fluid aliquot underwent fungal DNA isolation and was analyzed by next-generation sequencing (NGS) methods for identification of fungal species. Results: Of 50 ascitic samples collected, five samples showed growth of Candida spp. in culture. After DNA isolation and ITS2 PCR, detectable amplification was achieved in 10 samples. Sequencing of the 50 patients' samples identified facultative pathogenic fungi in 19 patients. In 15 cases, culture alone would not have permitted the identification of all facultative pathogenic fungi. The identification of fungal DNA by sequencing was significantly associated with poor patient outcome and a number of clinical parameters. Conclusions: Our results show a higher sensitivity for NGS-based diagnostic methods in the identification of ascitic fluid fungal infections compared to culture-based diagnostics. This may be beneficial especially for patients in a critical care setting, who have an increased prevalence of comorbidities and high mortality. The implementation of such methods in standard diagnosis will require increased standardization of the workflows and interpretation of the sequencing results with respect to patients' clinical picture. [ABSTRACT FROM AUTHOR]

Medical microbiology laboratories play an essential role in patient care—appertaining to infectious diseases diagnostics and treatment, infection prevention, and antimicrobial stewardship. Collaboration between clinicians and the microbiology laboratory can promote and enhance the safety, quality, and efficiency of patient care. We review practical, evidence-informed core concepts to explicate how effective partnership between clinicians and the microbiology laboratory improves patient outcomes. [ABSTRACT FROM AUTHOR]

Objectives: Clinical microbiologists require easy-to-use open access tools with graphical interfaces to perform bacterial whole-genome sequencing (WGS) in routine practice. This study aimed to build a bioinformatics pipeline on the open-source Galaxy platform, facilitating comprehensive and reproducible analysis of bacterial WGS data in a few steps. We then used it to characterize our local epidemiology of ESBL-producing Enterobacterales isolated from patients with bacteremia. Methods: We built a bioinformatics pipeline consisting of the following sequential tools: Fastp (input data trimming); FastQC (read quality control); SPAdes (genome assembly); Quast (quality control of genome assembly); Prokka (gene annotation); Staramr (ResFinder database) and ABRicate (CARD database) for antimicrobial resistance (AMR) gene screening and molecular strain typing. Paired-end short read WGS data from all ESBL-producing Enterobacterales strains isolated from patients with bacteremia over one year were analysed. Results: The Galaxy platform does not require command line tools. The bioinformatics pipeline was constructed within one hour. It only required uploading fastq files and facilitated systematization of de novo assembly of genomes, MLST typing, and AMR gene screening in one step. Among the 66 ESBL-producing strains analysed, the two most frequent ESBL genes were blaCTX−M-15 (62.1%) and blaCTX−M-27 (13.6%). Conclusions: The open-access Galaxy platform provides a graphical interface and easy-to-use tools suitable for routine use in clinical microbiology laboratories without bioinformatics specialists. We believe that this platform will facilitate fast and low-cost analysis of bacterial WGS data, especially in resource-limited settings.

Aims A severe lockdown occurred in Wuhan during the COVID-19 pandemic, followed by a remission phase in the pandemic's aftermath. This study analyzed the bacterial and fungal profiles of respiratory pathogens in patients hospitalized with non-COVID-19 lower respiratory tract infections (LRTIs) during this period to determine the pathogen profile distributions in different age groups and hospital departments in Wuhan. Methods and results We collected reports of pathogen testing in the medical records of patients hospitalized with non-COVID-19 LRTI between 2019 and 2021. These cases were tested for bacterial and fungal pathogens using 16S and internal transcribed spacer sequencing methods on bronchoalveolar lavage fluid samples. The study included 1368 cases. The bacteria most commonly identified were Streptococcus pneumoniae (12.50%) and Mycoplasma pneumoniae (8.33%). The most commonly identified fungi were Aspergillus fumigatus (2.49%) and Pneumocystis jirovecii (1.75%). Compared to 2019, the S. pneumoniae detection rates increased significantly in 2021, and those of M. pneumoniae decreased. Streptococcus pneumoniae was detected mainly in children. The detection rates of almost all fungi were greater in the respiratory Intensive Care Unit compared to respiratory medicine. Streptococcus pneumoniae and M. pneumoniae were detected more frequently in the pediatric department. Conclusions Before and after the COVID-19 outbreak, a change in the common pathogen spectrum was detected in patients with non-COVID-19 in Wuhan, with the greatest change occurring among children. The major pathogens varied by the patient's age and the hospital department. [ABSTRACT FROM AUTHOR]

Introduction: Extraintestinal Escherichia coli infections represent a growing public health threat, However, current studies often overlook important factors such as temporal patterns of infection, phylogenetic and clonal background, or the host gut E. coli population, despite their likely significance. Methods: In this study, we analyzed >7000 clinical E. coli isolates from patients at the Minneapolis Veterans Affairs Health Care System (2012-2019), and concurrent fecal E. coli from uninfected veterans. We assessed phylogenetic group distribution, membership in selected sequence types (STs), and subsets thereof--including the pandemic, resistance-associated ST131-H30R, and ST1193 lineages--and strain type, as defined by pulsed-field gel electrophoresis. We then analyzed these features alongside the temporal patterns of infection in individual hosts. Results: The H30R lineage emerged as the leading lineage, both overall and among fluoroquinolone-resistant isolates, with ST1193 following among fluoroquinolone-resistant isolates. Recurrences were common, occurring in 31% of subjects and 41% of episodes, and often multiple and delayed/prolonged (up to 23 episodes per subject; up to 2655d post-index). Remarkably, these recurrences typically involved the subject's index strain (63% of recurrences), even when affecting extra-urinary sites. ST131, H30R, ST1193, and fluoroquinoloneresistant strains generally caused significantly more recurrences than did other strains, despite similar recurrence intervals. ST131 strain types shifted significantly over the study period. Infection-causing strains were commonly detectable in host feces at times other than during an infection episode; the likelihood of detection varied with surveillance intensity and proximity to the infection. H30R and ST1193 were prominent causes of fecal-clinical clonal overlap. Discussion: These findings provide novel insights into the temporal and clonal characteristics of E. coli infections in veterans and support efforts to develop anti-colonization interventions. [ABSTRACT FROM AUTHOR]

The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs. [ABSTRACT FROM AUTHOR]

Microbial analytical methods have been instrumental in elucidating the complex microbial etiology of periodontal diseases, by shaping our understanding of subgingival community dynamics. Certain pathobionts can orchestrate the establishment of dysbiotic communities that can subvert the host immune system, triggering inflammation and tissue destruction. Yet, diagnosis and management of periodontal conditions still rely on clinical and radiographic examinations, overlooking the well‐established microbial etiology. This review summarizes the chronological emergence of periodontal etiological models and the co‐evolution with technological advances in microbial detection. We additionally review the microbial analytical approaches currently accessible to clinicians, highlighting their value in broadening the periodontal assessment. The epidemiological importance of obtaining culture‐based antimicrobial susceptibility profiles of periodontal taxa for antibiotic resistance surveillance is also underscored, together with clinically relevant analytical approaches to guide antibiotherapy choices, when necessary. Furthermore, the importance of 16S‐based community and shotgun metagenomic profiling is discussed in outlining dysbiotic microbial signatures. Because dysbiosis precedes periodontal damage, biomarker identification offers early diagnostic possibilities to forestall disease relapses during maintenance. Altogether, this review highlights the underutilized potential of clinical microbiology in periodontology, spotlighting the clinical areas most conductive to its diagnostic implementation for enhancing prevention, treatment predictability, and addressing global antibiotic resistance. [ABSTRACT FROM AUTHOR]

ABSTRACT Blood cultures are central to the management of patients with sepsis and bloodstream infection. Clinical decisions depend on the timely availability of laboratory information, which, in turn, depends on the optimal laboratory processing of specimens. Discrete event simulation (DES) offers insights into where optimization efforts can be targeted. Here, we generate a detailed process map of blood culture processing within a laboratory and use it to build a simulator. Direct observation of laboratory staff processing blood cultures was used to generate a flowchart of the blood culture laboratory pathway. Retrospective routinely collected data were combined with direct observations to generate probability distributions over the time taken for each event. These data were used to inform the DES model. A sensitivity analysis explored the impact of staff availability on turnaround times. A flowchart of the blood culture pathway was constructed, spanning labeling, incubation, organism identification, and antimicrobial susceptibility testing. Thirteen processes in earlier stages of the pathway, not otherwise captured by routinely collected data, were timed using direct observations. Observations revealed that specimen processing is predominantly batched. Another eight processes were timed using retrospective data. A simulator was built using DES. Sensitivity analysis revealed that specimen progression through the simulation was especially sensitive to laboratory technician availability. Gram stain reporting time was also sensitive to laboratory scientist availability. Our laboratory simulation model has wide-ranging applications for the optimization of laboratory processes and effective implementation of the changes required for faster and more accurate results.IMPORTANCEOptimization of laboratory pathways and resource availability has a direct impact on the clinical management of patients with bloodstream infection. This research offers an insight into the laboratory processing of blood cultures at a system level and allows clinical microbiology laboratories to explore the impact of changes to processes and resources.

ObjectivesAscites, often associated with critical pathologies such as liver cirrhosis or bowel perforation, can be complicated by fungal infection, increasing mortality especially in intensive care settings and demanding rapid diagnosis and adequate treatment. Traditional microbiological diagnostic methods have limited sensitivity in accurately identifying fungal pathogens in ascitic fluid. Alternative diagnostic methods may offer important insights to enable guiding of antifungal therapy and refining empirical treatment strategies. The objective of this study was to evaluate the potential of next-generation sequencing methods to identify specific fungal pathogens responsible for ascitic fluid infections.MethodsWe prospectively collected 50 ascitic fluid samples from ICU patients with suspected ascites infection. In addition to standard culture-based microbiological testing, an ascitic fluid aliquot underwent fungal DNA isolation and was analyzed by next-generation sequencing (NGS) methods for identification of fungal species.ResultsOf 50 ascitic samples collected, five samples showed growth of Candida spp. in culture. After DNA isolation and ITS2 PCR, detectable amplification was achieved in 10 samples. Sequencing of the 50 patients’ samples identified facultative pathogenic fungi in 19 patients. In 15 cases, culture alone would not have permitted the identification of all facultative pathogenic fungi. The identification of fungal DNA by sequencing was significantly associated with poor patient outcome and a number of clinical parameters.ConclusionsOur results show a higher sensitivity for NGS-based diagnostic methods in the identification of ascitic fluid fungal infections compared to culture-based diagnostics. This may be beneficial especially for patients in a critical care setting, who have an increased prevalence of comorbidities and high mortality. The implementation of such methods in standard diagnosis will require increased standardization of the workflows and interpretation of the sequencing results with respect to patients’ clinical picture.

Summary: Antimicrobial resistance poses a serious threat to global public health. The COVID-19 pandemic underscored the need to monitor the dissemination of antimicrobial resistance genes and understand the mechanisms driving this process. In this study, we analyzed changes to the oropharyngeal and fecal resistomes of patients with COVID-19 undergoing therapy in a hospital setting. A targeted sequencing panel of 4,937 resistance genes was used to comprehensively characterize resistomes. Our results demonstrated that the oropharyngeal resistome is homogeneous, showing low variability over time. In contrast, fecal samples clustered into two distinct resistotypes that were only partially related to enterotypes. Approximately half of the patients changed their resistotype within a week of therapy, with the majority transitioning to a less diverse and ermB-dominated resistotype 2. Common macrolide resistance genes were identified in over 80% of both oropharyngeal and fecal samples, likely originating from streptococci. Our findings suggest that the fecal resistome is a dynamic system that can exist in certain “states” and is capable of transitioning from one state to another. To date, this is the first study to comprehensively describe the oropharyngeal resistome and its variability over time, and one of the first studies to demonstrate the temporal dynamics of the fecal resistotypes.

Background In 2022, the global dissemination of mpox virus (MPXV) outside endemic regions prompted the expansion of diagnostic testing worldwide. This study assesses the performance characteristics of 5 real-time polymerase chain reaction (PCR) assays in detecting MPXV during the 2022 outbreak. Methods Clinical specimens collected from patients across Ontario, Canada, were tested on the following assays: RealStar Orthopoxyvirus PCR and FlexStar Monkeypox virus PCR (Altona Diagnostics), Novaplex MPXV (Seegene), VIASURE Monkeypox virus Real Time PCR Reagents (CerTest Biotec), and a laboratory-developed test. Positive percent agreement (PPA), negative percent agreement (NPA), relative limit of detection (LOD), and precision were evaluated and MPXV lineages were determined using an amplicon-based whole-genome sequencing (WGS) assay. Results Swabs were collected from various anatomic sites (65 positive and 30 negative). All assays demonstrated 100% NPA (95% confidence interval, 88.4%/88.1%–100.0%), with PPA ranging from 92.2% (82.7%–97.4%) to 96.9% (89.3%–99.6%). LOD and precision were comparable across assays, with coefficient of variations <3%. WGS analysis identified 6 lineages, all belonging to subclade IIb. Conclusions The assays exhibited excellent PPA, NPA, LOD, and precision. Ongoing performance monitoring is essential to detect assay escape mutants and ensure universal detection of evolving MPXV strains. [ABSTRACT FROM AUTHOR]

MALDI-ToF MS has become a cornerstone of the clinical microbiology laboratory. The reliability and ease-of-use of these instruments make them a popular choice of study to expand their applications and increase efficiency. The use of artificial intelligence has rapidly expanded in recent years and efforts are underway to integrate this technology into the clinical microbiology laboratory to expand the applications of MALDI-ToF MS and advance beyond current limitations in the identification of clinical isolates. At the same time as the rise of AI, clinical laboratories are facing pressure to increase efficiency due to the critical shortage of qualified laboratory personnel. Studies examining the performance of simplified testing workflows seek to help laboratorians do more with less. The improvement and creation of additional databases is also improving the rate of successful identifications. This review seeks to provide an update on recent developments around these topics. [ABSTRACT FROM AUTHOR]

Diagnostic laboratories in Aotearoa, New Zealand (NZ) refer cultures from faecal samples positive for Shiga toxin genes to the national Enteric Reference Laboratory for isolation of Shiga toxin-producing Escherichia coli (STEC) for epidemiological typing. As there was variation in the culture media being referred, a panel of 75 clinical isolates of STEC, representing 28 different serotypes, was used to assess six commercially available media and provide guidance to clinical laboratories. Recommendations were subsequently tested for a 3-month period, where STEC isolations and confirmations were assessed by whole genome sequencing analysis against the culture media referred. CHROMagar™ STEC (CH-STEC; CHROMagar Microbiology, Paris, France) or CH-STEC plus cefixime-tellurite sorbitol MacConkey agar was confirmed inferior to CH-STEC plus blood agar with vancomycin, cefsulodin, and cefixime (BVCC). The former resulted in fewer STEC types (n  = 18) being confirmed compared to those from a combination of CH-STEC and BVCC (n  = 42). A significant (P  < .05) association with an STEC's ability to grow on CH-STEC and the presence of the ter gene cluster, and eae was observed. Culturing screen positive STEC samples onto both CH-STEC and BVCC ensures a consistently higher recovery of STEC from all clinical samples in NZ than CH-STEC alone. [ABSTRACT FROM AUTHOR]

L'arrivée du séquençage à haut débit en microbiologie clinique ouvre la voie à de nouvelles approches diagnostiques et pronostiques dans le domaine des maladies infectieuses. La détection, l'identification et la caractérisation des microorganismes pathogènes constituent les étapes majeures dans le diagnostic et la mise en place d'un traitement antimicrobien adapté. Cependant, les méthodes standard de diagnostic microbiologique sont dans certains cas prises en défaut. De plus, l'émergence de nouvelles infections, favorisée par les voyages internationaux et le réchauffement climatique, rendent nécessaire la mise en place de méthodes de diagnostic innovantes. Parmi les différentes stratégies utilisées en microbiologie clinique et exposées dans cet article, la métagénomique shotgun est la seule technique permettant aujourd'hui une détection panpathogène et sans a priori, c'est-à-dire de l'ensemble des microorganismes potentiellement responsables d'une maladie infectieuse, incluant ceux encore inconnus. Cet article a pour objectifs d'exposer les différentes stratégies possibles du séquençage à haut débit utilisé dans le diagnostic microbiologique des maladies infectieuses, et de mettre en avant la contribution diagnostique de la métagénomique shotgun dans le domaine des infections du système nerveux central. The advent of high-throughput sequencing in clinical microbiology is opening the way to new diagnostic and prognostic approaches in infectious diseases. Detection, identification and characterisation of pathogenic microorganisms are essential steps in diagnosis and implementation of appropriate antimicrobial therapy. However, standard methods of microbiological diagnosis are failing in some cases. In addition, the emergence of new infections, facilitated by international travel and global warming, requires the implementation of innovative diagnostic methods. Among the different strategies used in clinical microbiology and reviewed in this article, shotgun metagenomics is the only technique that allows today a panpathogenic and unbiased detection of all microorganisms potentially responsible for an infectious disease, including those still unknown. The aims of this article are to present the different possible strategies of high-throughput sequencing used in the microbiological diagnosis of infectious diseases and to highlight the diagnostic contribution of shotgun metagenomics in the field of central nervous system infections. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), described as computer algorithms that exhibit cognitive characteristics like learning abilities, now affecting our lives in many areas. In the medical field, AI-supported image analysis has already taken on a central role in pathology, radiology and dermatology. The policy of this review consisted of peer-reviewed literature annotated in the Web of Science, Scopus, PubMed and Google Scholar databases. Articles were reviewed that describe the use of AI to analyze images to diagnose infectious diseases. Digitization in healthcare is already having a profound impact on patients. It is expected that the development that has started will continue to gain momentum. Machine learning is fundamentally changing the way we interact with health-related data, including clinical microbiology and infectious disease data. We will likely transition from the Internet of Things environment to the Internet of Bodies with devices and providing detailed health data even in disease-free times. The focus of this study was to review current views on attempts to apply AI methods in daily practice, as well as to search for promising methods to diagnose infectious diseases in the most efficient way. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus infections have already presented a substantial public health challenge, encompassing different clinical manifestations, ranging from bacteremia to sepsis and multi-organ failures. Among these infections, methicillin-resistant S. aureus (MRSA) is particularly alarming due to its welldocumented resistance to multiple classes of antibiotics, contributing significantly to global mortality rates. Consequently, the urgent need for effective treatment options has prompted a growing interest in exploring phage therapy as a potential non-antibiotic treatment against MRSA infections. Phages represent a class of highly specific bacterial viruses known for their ability to infect certain bacterial strains. This review paper explores the clinical potential of phages as a treatment for MRSA infections due to their low toxicity and auto-dosing capabilities. The paper also discusses the synergistic effect of phage-antibiotic combination (PAC) and the promising results from in vitro and animal model studies, which could lead to extensive human clinical trials. However, clinicians need to establish and adhere to standard protocols governing phage administration and implementation. Prominent clinical trials are needed to develop and advance phage therapy as a non-antibiotic therapy intervention, meeting regulatory guidelines, logistical requirements, and ethical considerations, potentially revolutionizing the treatment of MRSA infections. [ABSTRACT FROM AUTHOR]

ABSTRACT The annual meeting for the Intermountain Branch was held in April 2024 on the campus of Brigham Young University. There were 127 branch members from Utah, Idaho, and Nevada who attended the meeting and were composed of undergraduate students, graduate or medical students, and faculty. This report highlights the diversity of, and the emerging trends in, the research conducted by American Society for Microbiology members in the Intermountain Branch.

Clinical Microbiology has developed during the last 100 years, simultaneous with the discovery of microorganisms as causes of infections. Globalization and One Health determine present needs whereas molecular biology, automation, artificial intelligence, and bioinformatics are new tools that characterize the new developments in the field.

Summary: Accurate detection of pathogens, particularly distinguishing between Gram-positive and Gram-negative bacteria, could improve disease treatment. Host gene expression can capture the immune system’s response to infections caused by various pathogens. Here, we present a deep neural network model, bvnGPS2, which incorporates the attention mechanism based on a large-scale integrated host transcriptome dataset to precisely identify Gram-positive and Gram-negative bacterial infections as well as viral infections. We performed analysis of 4,949 blood samples across 40 cohorts from 10 countries using our previously designed omics data integration method, iPAGE, to select discriminant gene pairs and train the bvnGPS2. The performance of the model was evaluated on six independent cohorts comprising 374 samples. Overall, our deep neural network model shows robust capability to accurately identify specific infections, paving the way for precise medicine strategies in infection treatment and potentially also for identifying subtypes of other diseases.

Phenotypic identification of bacteria by staining technique and biochemical tests. This practical was carried out to identify Proteus vulgaris using biochemical test, this test includes, citrate utilization, indole, carbohydrate fermentation, methyl red, voges Proskauer, motility, production of hydrogen sulphide, catalase, and oxidase tests. Results obtained shows that Proteus vulgaris was positive to indole, motility, methyl red and urease. Proteus vulgaris was unable to utilize citrate for carbon and energy, and does not synthesis the enzyme amylase to break down starch. The bacteria fermented glucose to produce acid and gas. [ABSTRACT FROM AUTHOR]

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Summary: Helicobacter pylori (H. pylori) infection is a known cause of many digestive diseases, including gastritis, peptic ulcers, and gastric cancer. However, the underlying mechanisms by which H. pylori infection triggers these disorders are still not clearly understood. Gastric cancer is a slow progressing disease, which makes it difficult to study. We have developed an accelerated disease progression mouse model, which leverages mice deficient in the myeloid differentiation primary response 88 gene (Myd88−/−) infected with Helicobacter felis (H. felis). Using this model and gastric biopsy samples from patients, we report that activation of the Toll/interleukin-1 receptor (TIR)-domain-containing adaptor inducing interferon-β (TRIF)-type I interferon (IFN-I) signaling pathway promotes Helicobacter-induced disease progression toward severe gastric pathology and gastric cancer development. Further, results implicated downstream targets of this pathway in disease pathogenesis. These findings may facilitate stratification of Helicobacter-infected patients and thus enable treatment prioritization of patients.

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally, this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, each being present at a pre-determined concentration, thereby determining if the sample isresistant or susceptible to each sample. The minimum inhibitory concentration (MIC) of a drug is the lowestconcentration that inhibits growth and is a more useful quantity but requires each sample to be tested at a range ofconcentrations for each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is still an expensive and slow process that requires highly-skilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

The NG-Test CARBA 5 and Carbapenem-resistant K.N.I.V.O. Detection K-Set are lateral flow assays (LFAs) that rapidly detect five carbapenemases (KPC, NDM, IMP, VIM and OXA-48-like). We evaluated the effect of inoculum size on the performance of these two assays using 27 Enterobacterales isolates. Whole-genome sequencing (WGS) was used as the reference method. Using the NG-Test CARBA 5, eight Serratia spp. and six M. morganii isolates showed false-positive NDM results with a high inoculum. Using the Carbapenem-resistant K.N.I.V.O. Detection K-Set, eight M. morganii, four Serratia spp. and one K. pneumoniae isolates showed false-positive NDM and/or OXA-48-like bands at large inoculum sizes, while the other two M. morganii isolates demonstrated false-positive NDM and OXA-48-like results at all inoculum sizes. The false-positive bands varied in intensity. WGS confirmed that no carbapenemase gene was present. No protein sequence with a ≥50% identity to NDM or OXA-48-like enzymes was found. This study emphasizes the importance of assessing inoculum size in the diagnostic evaluation of LFAs.

ABSTRACT Untreated asymptomatic bacteriuria (ASB) has been associated with adverse pregnancy outcomes. Thus, routine screening by standard urine culture (SUC) and treatment of ASB are currently recommended for all pregnant women. However, SUC often misses microbes detected by expanded quantitative urine culture methods (EQUC) and 16S rRNA gene (amplicon) sequencing. The existence of these microbes (urinary microbiome) challenges the current approach to ASB screening in pregnancy as it is limited by two assumptions: (i) the female bladder is naturally sterile and (ii) SUC identifies all clinically relevant uropathogens. To determine the uniqueness or similarity between urinary and vaginal microbiomes, we performed a prospective observational institutional review board (IRB)-approved cohort study of pregnant women with a singleton pregnancy

Summary: Central nervous sequelae are often reported in recovered patients with COVID-19. It is not clear whether recovered COVID-19 patients have glymphatic impairment and clinical correlation. In this study, we demonstrated that mild COVID-19 patients experienced asymmetric bilateral glymphatic function decline after four months of recovery, and the decrease in glymphatic function was more obvious in older recovered patients. Our results further showed that recovered patients with right-sided glymphatic dysfunction experienced a greater proportion of cognitive decline (MoCA score

BackgroundCollecting data on antimicrobial resistance (AMR) is an essential approach for defining the scope of the AMR problem, developing evidence-based interventions and detecting new and emerging resistances. Our study aimed to identify key factors influencing the implementation of a laboratory-based AMR surveillance system in Cambodia. This will add additional insights to the development of a sustainable and effective national AMR surveillance system in Cambodia and other low- and middle-income countries.MethodsKey informants with a role in governing or contributing data to the laboratory-based surveillance system were interviewed. Emerging themes were identified using the framework analysis method. Laboratories contributing to the AMR surveillance system were assessed on their capacity to conduct quality testing and report data. The laboratory assessment tool (LAT), developed by the World Health Organisation (WHO), was adapted for assessment of a diagnostic microbiology laboratory covering quality management, financial and human resources, data management, microbiology testing performance and surveillance capacity.ResultsKey informants identified inadequate access to laboratory supplies, an unsustainable financing system, limited capacity to collect representative data and a weak workforce to be the main barriers to implementing an effective surveillance system. Consistent engagement between microbiology staff and clinicians were reported to be a key factor in generating more representative data for the surveillance system. The laboratory assessments identified issues with quality assurance and data analysis which may reduce the quality of data being sent to the surveillance system and limit the facility-level utilisation of aggregated data. A weak surveillance network and poor guidance for outbreak response were also identified, which can reduce the laboratories’ opportunities in detecting critical or emerging resistance occurring in the community or outside of the hospital’s geographical coverage.ConclusionThis study identified two primary concerns: ensuring a sustainable and quality functioning of microbiology services at public healthcare facilities and overcoming sampling bias at sentinel sites. These issues hinder Cambodia’s national AMR surveillance system from generating reliable evidence to incorporate into public health measures or clinical interventions. These findings suggest that more investments need to be made into microbiology diagnostics and to reform current surveillance strategies for enhanced sampling of AMR cases at hospitals.

Clinically we have been aware of the concept of Candida biofilms for many decades, though perhaps without the formal designation. Just over 20 years ago the subject emerged on the back of progress made from the bacterial biofilms, and academic progress pace has continued to mirror the bacterial biofilm community, albeit at a decreased volume. It is apparent that Candida species have a considerable capacity to colonize surfaces and interfaces and form tenacious biofilm structures, either alone or in mixed species communities. From the oral cavity, to the respiratory and genitourinary tracts, wounds, or in and around a plethora of biomedical devices, the scope of these infections is vast. These are highly tolerant to antifungal therapies that has a measurable impact on clinical management. This review aims to provide a comprehensive overight of our current clinical understanding of where these biofilms cause infections, and we discuss existing and emerging antifungal therapies and strategies. [ABSTRACT FROM AUTHOR]

Background: Matrix-assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) is one of the preferred detection techniques for identification of clinical microorganisms and it has the characteristics of rapid identification, simple operation, low cost, and updatable databases. For laboratory medicine undergraduates, clinical internship is an important stage for the connection of basic theoretical knowledge and clinical practice. Internship teaching choosing MALDI-TOF MS as the content will greatly increase the popularity and applicability of the new technology in the clinical microbiology laboratory. Methods: With the help of electronic databases on the network, we conducted a systematic review. According to the purpose of research, we singled out forty papers. Latest studies on history, basic principles, clinical features, and applications of MALDI-TOF MS and the internship teaching contents introducing new technologies are summarized and focused on. In internship teaching, firstly we explain the historical development, basic principle and widespread applications of MALDI-TOF MS in the identification of clinical pathogenic microorganisms and the detection of antibiotic resistance. Subsequently, we instruct the students to perform the experimental operations, analyze the common problems, and find solutions. Finally, we highlight quality control and laboratory biosafety. Results: Most of the reviews published previously report the clinical features and applications of MALDI-TOF MS and the internship teaching contents choosing other new technologies. It is the first study selecting MALDI-TOF MS technology as an internship teaching content creatively. Primary outcome is that the students understand the theoretical knowledge in detail, master the operation skills of MALDI-TOF MS quickly, and obtain excellent internship performances in the clinical internship through the internship teaching. Secondary outcome is that it is a help to cultivate medical students' train of thought for scientific research and to understand the application of the new technology in clinical testing and scientific research. Conclusions: Laboratory medicine undergraduates should cherish the opportunity to learn the new technology during the internship period and should master basic principle and operation. As internship teachers, it is necessary to introduce the new technology to students during the internship and encourage undergraduates to cultivate creative and innovative thinking of scientific research. [ABSTRACT FROM AUTHOR]

Introduction: Various studies have demonstrated a clear link between mucosa-adherent Escherichia coli and colorectal cancer (CRC). This in silico study aims to identify commonly differentially expressed genes in CRC cells treated with distinct E. coli strains, regardless of their pathogenicity. Methods: The raw data from the GEO database were normalized with the Affy package in the R software. We used computational methods (limma analysis, linear regression analysis, hierarchical clustering, and gene set enrichment analysis) to identify the transcriptome alterations induced by E. coli O:157.H7 and E. coli K-12 strains. Results: Out of the 80 genes that were significantly differentially expressed in both E. coli-treated groups, only three genes (HIST1H4E, JUN, and TMEM267) demonstrated a high correlation (r>0.9) with the incubation time. TMEM267 is downregulated as the incubation time increases whereas HIST1H4E and JUN become upregulated. In addition, we determined nine common genesets that were significantly enriched in the Caco2 cell line after treatment either with E.coli O:157.H7 or K-12 strains. Discussion and Conclusion: In this study, the changes in gene expressions resulting from the treatment of colon cancer cells with different E. coli strains were investigated. These findings highlight the potential impact of E. coli on cancer development and suggest that certain genes may play a role in mediating the effects of E. coli in the context of CRC. Further research is warranted to elucidate the underlying mechanisms and specific pathways involved in the interactions between E. coli and cancer cells. [ABSTRACT FROM AUTHOR]

Professor Henrik C. Wegener, Rector of the University of Copenhagen, writes about the impact of Louis Pasteur and his legacy as a role model in science at the centennial of the Danish Pasteur Society and the bicentennial of Pasteur's birth. [ABSTRACT FROM AUTHOR]

Summary: The emergence and spread of new SARS-CoV-2 variants with mutations in the spike protein, such as the XBB.1.5 and XBB.1.9.1 sublineages, raise concerns about the efficacy of current COVID-19 vaccines and therapeutic monoclonal antibodies (mAbs). In this study, none of the mAbs we tested neutralized XBB.1.9.1 or XBB.1.5, even at the highest concentration used. We also found that the bivalent mRNA vaccine could enhance humoral immunity against XBB.1.9.1, but that XBB.1.9.1 and XBB.1.5 still evaded humoral immunity induced by vaccination or infection. Moreover, the susceptibility of XBB.1.9.1 to remdesivir, molnupiravir, nirmatrelvir, and ensitrelvir was similar to that of the ancestral strain and the XBB.1.5 isolate in vitro. Finally, we found the replicative fitness of XBB.1.9.1 to be similar to that of XBB.1.5 in hamsters. Our results suggest that XBB.1.9.1 and XBB.1.5 have similar antigenicity and replicative ability, and that the currently available COVID-19 antivirals remain effective against XBB.1.9.1.

Community-acquired pneumonia (CAP) remains the leading cause of hospitalization among infectious disease in Europe, and a major cause of morbidity and mortality. In order to determine and characterize the aetiology of CAP in hospitalized adults in Cyprus, respiratory and blood samples were obtained from hospitalized patients with CAP, and analyzed using Multiplex Real-Time PCR/RT-PCR, and ID/AMR enrichment panel (RPIP) analysis. Probe-based allelic discrimination was used to investigate genetic host factors in patients. The aetiology could be established in 87% of patients. The most prevalent viral pathogens detected were influenza A, SARS-CoV-2, and human rhinovirus. The most common bacterial pathogens detected were Streptococcus pneumoniae, Staphylococcus aureus, and Haemophilus influenzae. Antimicrobial resistance genes were identified in 23 patients. S. aureus was the most common AMR correlated strain in our study. A positive correlation was detected between bacterial infections and the NOS3 rs1799983 G allele and the FCGR2A rs1801274 G allele. A positive correlation was also detected between the TNF-α rs1800629 A allele and sepsis, while a negative correlation was detected with the ACE rs1799752 insertion genotype and the severity of pneumonia. In conclusion, the targeted NGS panel approach applied provides highly sensitive, comprehensive pathogen detection, in combination with antimicrobial resistance AMR insights that can guide treatment choices. In addition, several host factors have been identified that impact the disease progression and outcome. [ABSTRACT FROM AUTHOR]

Shiga toxin (stx)‐producing Escherichia coli (STEC) causes potentially severe gastrointestinal infections. Due to its public health importance, control measures are required, and carriers may need to refrain from work or daycare when the risk of spread to vulnerable people is high. We evaluated the use of direct stool multiplex PCR compared to culture for primary STEC diagnostics and for follow‐up in order to update the national guidelines for STEC monitoring. We analyzed primary and follow‐up samples of 236 STEC PCR‐positive cases at HUSLAB, Helsinki, Finland in 2016–2017, altogether 858 samples. All STEC PCR‐positive samples were inoculated on non‐selective chromogenic agar plates. Culture positivity was confirmed from culture sweeps by PCR. 211 (89%) of the cases were culture positive in their primary sample. Of all primary and follow‐up samples, 499 were PCR positive and of these 450 (90%) were culture positive. PCR‐negative follow‐up samples were available from 125 cases. Of these, 88 cases were followed for at least three consecutive PCR‐negative samples. Two cases (2%) had culture‐positive sample(s) after two consecutive PCR‐negative samples. The median time for STEC clearance was 22–23 days. The laboratory‐developed multiplex PCR test used in this study is a reliable method for STEC diagnostics and follow‐up in a clinical laboratory. When non‐selective methodology is used, the majority of PCR‐positive samples (90%) are also culture positive. Furthermore, only two cases (2%) in our material had two consecutive PCR‐negative samples followed by positive samples. Consequently, to demonstrate the clearance from STEC infection, we consider two PCR‐negative follow‐up samples sufficient. The Finnish national guidelines for STEC monitoring have been updated accordingly. [ABSTRACT FROM AUTHOR]

Mycoplasma genitalium is a sexually transmitted infection with increasing concerns around antimicrobial resistance. Droplet digital PCR (ddPCR) is a rapid quantification method with high precision that may be useful for absolute quantitation of bacteria in samples. This study aimed to develop a ddPCR assay for the quantification of M. genitalium. ddPCR targeting the gene mgpB was established and analysed using the QX100 ddPCR system. The assay was evaluated against quantitated DNA standards, and then in comparison to an established quantitative PCR performed on the Lightcycler 480 II. DNA template of increasing complexity was used, including synthetic double stranded DNA, DNA extracts from laboratory-cultured M. genitalium strains (n  = 17) and DNA from M. genitalium -positive clinical samples (n  = 21). There was a strong correlation between ddPCR concentration estimates and measured DNA standards (r 2 = 0.997), and between ddPCR and qPCR quantitation for different templates (r 2 ranging from 0.953 to 0.997). ddPCR reliably detected template in a range from <10 copies per reaction to >104 copies per reaction and demonstrated linearity over dilution series. Concentration estimates by ddPCR were reproducibly less than those determine by qPCR. ddPCR demonstrated precise and reproducible quantitation of M. genitalium with a variety of templates. [ABSTRACT FROM AUTHOR]

Abstract Background The rapidly growing area of sequencing technologies, and more specifically bacterial whole-genome sequencing, could offer applications in clinical microbiology, including species identification of bacteria, prediction of genetic antibiotic susceptibility and virulence genes simultaneously. To accomplish the aforementioned points, the commercial cloud-based platform, 1928 platform (1928 Diagnostics, Gothenburg, Sweden) was benchmarked against an in-house developed bioinformatic pipeline as well as to reference methods in the clinical laboratory. Methods Whole-genome sequencing data retrieved from 264 Staphylococcus aureus isolates using the Illumina HiSeq X next-generation sequencing technology was used. The S. aureus isolates were collected during a prospective observational study of community-onset severe sepsis and septic shock in adults at Skaraborg Hospital, in the western region of Sweden. The collected isolates were characterized according to accredited laboratory methods i.e., species identification by MALDI-TOF MS analysis and phenotypic antibiotic susceptibility testing (AST) by following the EUCAST guidelines. Concordance between laboratory methods and bioinformatic tools, as well as concordance between the bioinformatic tools was assessed by calculating the percent of agreement. Results There was an overall high agreement between predicted genotypic AST and phenotypic AST results, 98.0% (989/1006, 95% CI 97.3–99.0). Nevertheless, the 1928 platform delivered predicted genotypic AST results with lower very major error rates but somewhat higher major error rates compared to the in-house pipeline. There were differences in processing times i.e., minutes versus hours, where the 1928 platform delivered the results faster. Furthermore, the bioinformatic workflows showed overall 99.4% (1267/1275, 95% CI 98.7–99.7) agreement in genetic prediction of the virulence gene characteristics and overall 97.9% (231/236, 95% CI 95.0–99.2%) agreement in predicting the sequence types (ST) of the S. aureus isolates. Conclusions Altogether, the benchmarking disclosed that both bioinformatic workflows are able to deliver results with high accuracy aiding diagnostics of severe infections caused by S. aureus. It also illustrates the need of international agreement on quality control and metrics to facilitate standardization of analytical approaches for whole-genome sequencing based predictions.

Clinical microbiology has possessed a marvellous past, an important present and a bright future. Western medicine modernization started with the discovery of bacterial pathogens, and from then, clinical bacteriology became a cornerstone of diagnostics. Today, clinical microbiology uses standard techniques including Gram stain morphology, in vitro culture, antigen and antibody assays, and molecular biology both to establish a diagnosis and monitor the progression of microbial infections. Clinical microbiology has played a critical role in pathogen detection and characterization for emerging infectious diseases as evidenced by the ongoing COVID-19 pandemic. Revolutionary changes are on the way in clinical microbiology with the application of “-omic” techniques, including transcriptomics and metabolomics, and optimization of clinical practice configurations to improve outcomes of patients with infectious diseases.

The aim of our study was to evaluate a protocol utilizing serum separator tubes (SST) to facilitate a faster, cost-effective, direct method for rapid sensitivity testing and identification of positive blood cultures. Spiked cultures were inoculated into either Becton Dickinson (BD) BACTECTM Aerobic Plus or Anaerobic/F bottles containing sterile human blood. Bottles were immediately processed when positive. A parallel study using patient isolates was used in which bacteria were pelleted by SST from positive blood cultures. For identification, a portion of the pellet was tested by matrix-assisted laser desorption/ionization as described by the manufacturer. MicroScan panels and Vitek 2 results were compared. Categorical agreement was used as comparison to standard subculture and/or polymerase chain reaction methods. No discordant identifications were observed, and 86% generated a successful identification when compared to subculture methods. For the Vitek 2, we observed a 99% essential agreement when compared to the subculture method. For the MicroScan Walkaway, we observed 94.9%, 97.4%, and 100% categorical agreement for MIC panels 53, 38, and MICroSTREP Plus 2, respectively. Turnaround times were reduced from 4 hours for identification and 11 hours for antimicrobial sensitivity testing. We conclude that the SST method results in timelier, actionable results for antimicrobial stewardship initiatives. [ABSTRACT FROM AUTHOR]

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ABSTRACT The emergence and explosive spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 highlighted the need to rapidly develop curated biobanks to inform the etiology, diagnosis, and treatment options for global outbreaks of communicable diseases. Recently, we undertook efforts to develop a repository of biospecimens from individuals aged 12 and older who were to be vaccinated against coronavirus disease 19 (COVID-19) with vaccines developed with support from the United States Government. We planned to establish 40 or more clinical study sites in at least six countries to collect biospecimens from 1,000 individuals, 75% of whom were to be SARS-CoV-2 naive at the time of enrollment. Specimens would be used to (i) ensure quality control of future diagnostic tests, (ii) understand immune responses to multiple COVID-19 vaccines, and (iii) provide reference reagents for the development of new drugs, biologics, and vaccines. Biospecimens included serum, plasma, whole blood, and nasal secretions. Large-volume collections of peripheral blood mononuclear cells (PBMCs) and defibrinated plasma were also planned for a subset of subjects. Participant sampling was planned at intervals prior to and following vaccination over a 1-year period. Here, we describe the selection of clinical sites for specimen collection and processing, standard operating procedure (SOP) development, design of a training program for tracking specimen quality, and specimen transport to a repository for interim storage. This approach allowed us to enroll our first participants within 21 weeks from the study’s initiation. Lessons learned from this experience should benefit the development of biobanks in response to future global epidemics. IMPORTANCE The ability to rapidly create a biobank of high-quality specimens in response to emergent infectious diseases is critical to allow for the development of prevention and treatment, as well as to effectively monitor the spread of the disease. In this paper, we report on a novel approach to getting global clinical sites up and running within a short time frame and to monitor the quality of specimens collected to ensure their value in future research efforts. Our results have important implications for the monitoring of the quality of biospecimens collected and to design effective interventions to address shortcomings, where needed.