Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis

BACKGROUND

Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen guided by drug susceptibility test (DST) results. In most settings, DST information is not available or is limited to isoniazid and fluoroquinolones. Whole genome sequencing could more accurately guide individualized treatment as the full drug resistance profile is obtained with a single test. Whole genome sequencing has not reached its full potential for patient care, in part due to the complexity of translating a resistance profile into the most effective individualized regimen.

METHODS

We developed a treatment recommender clinical decision support system (CDSS) and an accompanying web application for user-friendly recommendation of the optimal individualized treatment regimen to a clinician.

RESULTS

Following expert stakeholder meetings and literature review, nine drug features and 14 treatment regimen features were identified and quantified. Using machine learning, a model was developed to predict the optimal treatment regimen based on a training set of 3895 treatment regimen-expert feedback pairs. The acceptability of the treatment recommender CDSS was assessed as part of a clinical trial and in a routine care setting. Within the clinical trial setting, all patients received the CDSS recommended treatment. In 8 of 20 cases, the initial recommendation was recomputed because of stock out, clinical contra-indication or toxicity. In routine care setting, physicians rejected the treatment recommendation in 7 out of 15 cases because it deviated from the national TB treatment guidelines. A survey indicated that the treatment recommender CDSS is easy to use and useful in clinical practice but requires digital infrastructure support and training.

CONCLUSIONS

Our findings suggest that global implementation of the novel treatment recommender CDSS holds the potential to improve treatment outcomes of patients with RR-TB, especially those with 'difficult-to-treat' forms of RR-TB.

Utility of next-generation sequencing for the etiological diagnosis of Orientia tsutsugamushi infection

Background

Scrub typhus, an acute febrile disease caused by Orientia tsutsugamushi, is transmitted to humans through infected chigger mites. We present a case of scrub typhus in a previously healthy man from Shandong Province diagnosed using next-generation sequencing (NGS) and PCR and review recent literature on NGS for scrub typhus diagnosis.

Methods

NGS was utilized for testing whole blood collected on admission. Confirmatory testing was done by detecting IgM and IgG antibodies to Orientia in acute and convalescent sera by ELISA. Orientia 47-kDa protein gene TaqMan and standard PCR of the 56-kDa protein gene and Sanger sequencing were performed on eschar scab DNA.

Results

The NGS diagnosis was confirmed by 47-kDa protein gene TaqMan and sequencing of a fragment of the O. tsutsugamushi 56-kDa protein gene from the eschar scab. Analysis of this sequence and the NGS data indicated O. tsutsugamushi strain Cheeloo2020 is a novel genotype. Mapping of the NGS data against the O. tsutsugamushi Gilliam strain genome sequence identified 304 reads with high similarity.

Conclusions

NGS is not only useful for multiplex diagnosis of scrub typhus, but also provides insight into the genetic diversity of O. tsutsugamushi. The common failure to submit sequences to databases makes it difficult to determine the minimal quantity and quality of NGS data being used for the positive identification of Orientia DNA in clinical specimens.

From Species to Genes: A New Diagnostic Paradigm

Molecular diagnostics has the potential to revolutionise the field of clinical microbiology. Microbial identification and nomenclature have, for too long, been restricted to phenotypic characterisation. However, this species-level view fails to wholly account for genetic heterogeneity, a result of lateral gene transfer, mediated primarily by mobile genetic elements. This genetic promiscuity has helped to drive virulence development, stress adaptation, and antimicrobial resistance in several important bacterial pathogens, complicating their detection and frustrating our ability to control them. We argue that, as clinical microbiologists at the front line, we must embrace the molecular technologies that allow us to focus specifically on the genetic elements that cause disease rather than the bacterial species that express them. This review focuses on the evolution of microbial taxonomy since the introduction of molecular sequencing, the role of mobile genetic elements in antimicrobial resistance, the current and emerging assays in clinical laboratories, and the comparison of phenotypic versus genotypic analyses. In essence, it is time now to refocus from species to genes as part of a new diagnostic paradigm.

Metagenomic next-generation sequencing promotes diagnosis and treatment of Pneumocystis jirovecii pneumonia in non-HIV infected children: a retrospective study

BACKGROUND

Metagenomic next-generation sequencing (mNGS) excels in diagnosis of infection pathogens. We aimed to evaluate the performance of mNGS for the diagnosis of Pneumocystis jirovecii pneumonia (PJP) in non-HIV infected children.

METHODS

Totally 36 PJP children and 61 non-PJP children admitted to the pediatric intensive care unit from March 2018 to December 2021 were retrospectively enrolled. Clinical features of PJP children were summarized. 1,3-β-D glucan (BDG) test and bronchoalveolar lavage fluid (BALF) mNGS were used for evaluation of PJP diagnostic performance. Antimicrobial management modifications for PJP children after the mNGS results were also reviewed.

RESULTS

Pneumocystis jirovecii was detected in all PJP children by mNGS (36/36), and the sensitivity of mNGS was 100% (95% confidence interval [CI]: 90.26-100%). The sensitivity of BDG was 57.58% (95% CI: 39.22-74.52%). Of the 26 (72.2%) PJP patients with mixed infection, twenty-four (66.7%) were detected by BALF-mNGS. Thirteen patients (36.1%) had their antimicrobial management adjusted according to the mNGS results. Thirty-six PJP children included 17 (47.2%) primary immunodeficiency and 19 (52.8%) secondary immunodeficiency, of whom 19 (52.8%) survived and 17 (47.2%) died. Compared to survival subgroup, non-survival subgroup had a higher rate of primary immunodeficiency (64.7% vs. 31.6%, P = 0.047), younger age (7 months vs. 39 months, P = 0.011), lower body weight (8.0 kg vs. 12.0 kg, P = 0.022), and lower T lymphocyte counts.

CONCLUSIONS

The mortality rate of PJP in immunosuppressed children without HIV infection is high and early diagnosis is challenging. BALF-mNGS could help identify PJP and guide clinical management.

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

Impact of Pericoronary Microbiota Composition on Course of Recovery after Third Molar Alveotomy

Although the role of microbiota has been investigated in relation to different oral diseases, it is unknown if its composition has any effect on the course of recovery after third molar alveotomy. Our aim was to determine the influence of patient clinical characteristics as well as pericoronary microbiota composition on the course of recovery after a semi-impacted third molar alveotomy. Thirty-six patients were included and samples obtained with paper points, swabs, and tissue samples were analyzed using DNA hybridization and culture methods. Among the 295 organisms detected, the most frequent were Streptococcus spp. (22.4%; 66/295) followed by Fusobacterium spp. (11.9%; 35/295), and T. forsythia (9.1%; 27/295). A comparison of microbiota composition in patients with better and worse recovery did not show significant differences. Worse recovery outcomes were more frequent in patients with a grade 2 self-assessment of oral health (p = 0.040) and better recovery courses were observed in patients with a grade 4 self-assessment (p = 0.0200). A worse recovery course was statistically significant more frequently in patients with previous oral surgical procedures (p = 0.019). Although we demonstrate that worse recovery outcomes were more frequent when certain bacteria were detected, there was no statistically significant difference. Further research is needed to identify microbial profiles specific to the development of worse outcomes after a third molar alveotomy.

GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes

BACKGROUND

Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options.

RESULTS

We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8-96.7%) to 79.6% for pyrazinamide (95% CI 76.9-82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1-100.0%) to 74.9% for capreomycin (95% CI 69.3-80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8-99.3%) to 79.5% for ethionamide (95% CI 76.4-82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC.

CONCLUSIONS

GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .

Automating the Illumina DNA library preparation kit for whole genome sequencing applications on the flowbot ONE liquid handler robot

Whole-genome sequencing (WGS) is currently making its transition from research tool into routine (clinical) diagnostic practice. The workflow for WGS includes the highly labor-intensive library preparations (LP), one of the most critical steps in the WGS procedure. Here, we describe the automation of the LP on the flowbot ONE robot to minimize the risk of human error and reduce hands-on time (HOT). For this, the robot was equipped, programmed, and optimized to perform the Illumina DNA Prep automatically. Results obtained from 16 LP that were performed both manually and automatically showed comparable library DNA yields (median of 1.5-fold difference), similar assembly quality values, and 100% concordance on the final core genome multilocus sequence typing results. In addition, reproducibility of results was confirmed by re-processing eight of the 16 LPs using the automated workflow. With the automated workflow, the HOT was reduced to 25 min compared to the 125 min needed when performing eight LPs using the manual workflow. The turn-around time was 170 and 200 min for the automated and manual workflow, respectively. In summary, the automated workflow on the flowbot ONE generates consistent results in terms of reliability and reproducibility, while significantly reducing HOT as compared to manual LP.

Virus sequencing performance during the SARS-CoV-2 pandemic: a retrospective analysis of data from multiple rounds of external quality assessment in Austria

Introduction: A notable feature of the 2019 coronavirus disease (COVID-19) pandemic was the widespread use of whole genome sequencing (WGS) to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Countries around the world relied on sequencing and other forms of variant detection to perform contact tracing and monitor changes in the virus genome, in the hopes that epidemic waves caused by variants would be detected and managed earlier. As sequencing was encouraged and rewarded by the government in Austria, but represented a new technicque for many laboratories, we designed an external quality assessment (EQA) scheme to monitor the accuracy of WGS and assist laboratories in validating their methods. Methods: We implemented SARS-CoV-2 WGS EQAs in Austria and report the results from 7 participants over 5 rounds from February 2021 until June 2023. The participants received sample material, sequenced genomes with routine methods, and provided the sequences as well as information about mutations and lineages. Participants were evaluated on the completeness and accuracy of the submitted sequence and the ability to analyze and interpret sequencing data. Results: The results indicate that performance was excellent with few exceptions, and these exceptions showed improvement over time. We extend our findings to infer that most publicly available sequences are accurate within ≤1 nucleotide, somewhat randomly distributed through the genome. Conclusion: WGS continues to be used for SARS-CoV-2 surveillance, and will likely be instrumental in future outbreak scenarios. We identified hurdles in building next-generation sequencing capacity in diagnostic laboratories. EQAs will help individual laboratories maintain high quality next-generation sequencing output, and strengthen variant monitoring and molecular epidemiology efforts.

An integrated method for targeted Oxford Nanopore sequencing and automated bioinformatics for the simultaneous detection of bacteria, fungi, and ARG

AIMS

The use of metagenomics for pathogen identification in clinical practice has been limited. Here we describe a workflow to encourage the clinical utility and potential of NGS for the screening of bacteria, fungi, and antimicrobial resistance genes (ARGs).

METHODS AND RESULTS

The method includes target enrichment, long-read sequencing, and automated bioinformatics. Evaluation of several tools and databases was undertaken across standard organisms (n = 12), clinical isolates (n = 114), and blood samples from patients with suspected bloodstream infections (n = 33). The strategy used could offset the presence of host background DNA, error rates of long-read sequencing, and provide accurate and reproducible detection of pathogens. Eleven targets could be successfully tested in a single assay. Organisms could be confidently identified considering ≥60% of best hits of a BLAST-based threshold of e-value 0.001 and a percent identity of >80%. For ARGs, reads with percent identity of >90% and >60% overlap of the complete gene could be confidently annotated. A kappa of 0.83 was observed compared to standard diagnostic methods. Thus, a workflow for the direct-from-sample, on-site sequencing combined with automated genomics was demonstrated to be reproducible.

CONCLUSION

NGS-based technologies overcome several limitations of current day diagnostics. Highly sensitive and comprehensive methods of pathogen screening are the need of the hour. We developed a framework for reliable, on-site, screening of pathogens.

Active surveillance of carbapenemase-producing Enterobacterales using genomic sequencing for hospital-based infection control interventions

BACKGROUND

Whole-genome sequencing (WGS) is increasingly used to characterize hospital outbreaks of carbapenemase-producing Enterobacterales (CPE). However, access to WGS is variable and testing is often centralized, leading to delays in reporting of results.

OBJECTIVE

We describe the utility of a local sequencing service to promptly respond to facility needs over an 8-year period.

METHODS

The study was conducted at Royal Prince Alfred Hospital in Sydney, Australia. All CPE isolated from patient (screening and clinical) and environmental samples from 2015 onward underwent prospective WGS. Results were notified to the infection control unit in real time. When outbreaks were identified, WGS reports were also provided to senior clinicians and the hospital executive administration. Enhanced infection control interventions were refined based on the genomic data.

RESULTS

In total, 141 CPE isolates were detected from 123 patients and 5 environmental samples. We identified 9 outbreaks, 4 of which occurred in high-risk wards (intensive care unit and/or solid-organ transplant ward). The largest outbreak involved Enterobacterales containing an NDM gene. WGS detected unexpected links among patients, which led to further investigation of epidemiological data that uncovered the outpatient setting and contaminated equipment as reservoirs for ongoing transmission. Targeted interventions as part of outbreak management halted further transmission.

CONCLUSIONS

WGS has transitioned from an emerging technology to an integral part of local CPE control strategies. Our results show the value of embedding this technology in routine surveillance, with timely reports generated in clinically relevant timeframes to inform and optimize local control measures for greatest impact.

Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies

Triple-Negative Breast Cancer (TNBC) presents a significant challenge in oncology due to its aggressive behavior and limited therapeutic options. This review explores the potential of immunotherapy, particularly vaccine-based approaches, in addressing TNBC. It delves into the role of immunoinformatics in creating effective vaccines against TNBC. The review first underscores the distinct attributes of TNBC and the importance of tumor antigens in vaccine development. It then elaborates on antigen detection techniques such as exome sequencing, HLA typing, and RNA sequencing, which are instrumental in identifying TNBC-specific antigens and selecting vaccine candidates. The discussion then shifts to the in-silico vaccine development process, encompassing antigen selection, epitope prediction, and rational vaccine design. This process merges computational simulations with immunological insights. The role of Artificial Intelligence (AI) in expediting the prediction of antigens and epitopes is also emphasized. The review concludes by encapsulating how Immunoinformatics can augment the design of TNBC vaccines, integrating tumor antigens, advanced detection methods, in-silico strategies, and AI-driven insights to advance TNBC immunotherapy. This could potentially pave the way for more targeted and efficacious treatments.

Comparison of genomic diversity between single and pooled Staphylococcus aureus colonies isolated from human colonization cultures

The most common approach to sampling the bacterial populations within an infected or colonized host is to sequence genomes from a single colony obtained from a culture plate. However, it is recognized that this method does not capture the genetic diversity in the population. Sequencing a mixture of several colonies (pool-seq) is a better approach to detect population heterogeneity, but it is more complex to analyse due to different types of heterogeneity, such as within-clone polymorphisms, multi-strain mixtures, multi-species mixtures and contamination. Here, we compared 8 single-colony isolates (singles) and pool-seq on a set of 2286 Staphylococcus aureus culture samples to identify features that can distinguish pure samples, samples undergoing intraclonal variation and mixed strain samples. The samples were obtained by swabbing 3 body sites on 85 human participants quarterly for a year, who initially presented with a methicillin-resistant S. aureus skin and soft-tissue infection (SSTI). We compared parameters such as sequence quality, contamination, allele frequency, nucleotide diversity and pangenome diversity in each pool to those for the corresponding singles. Comparing singles from the same culture plate, we found that 18% of sample collections contained mixtures of multiple multilocus sequence types (MLSTs or STs). We showed that pool-seq data alone could predict the presence of multi-ST populations with 95% accuracy. We also showed that pool-seq could be used to estimate the number of intra-clonal polymorphic sites in the population. Additionally, we found that the pool may contain clinically relevant genes such as antimicrobial resistance markers that may be missed when only examining singles. These results highlight the potential advantage of analysing genome sequences of total populations obtained from clinical cultures rather than single colonies.

Multidrug-resistant Escherichia coli isolated from patients and surrounding hospital environments in Bangladesh: A molecular approach for the determination of pathogenicity and resistance

Extended spectrum β-lactamase producing Escherichia coli (ESBL E. coli) is a primary concern for hospital and community healthcare settings, often linked to an increased incidence of nosocomial infections. This study investigated the characteristics of ESBL E. coli isolated from hospital environments and clinical samples. In total, 117 ESBL E. coli isolates were obtained. The isolates were subjected to molecular analysis for the presence of resistance and virulence genes, antibiotic susceptibility testing, quantitative adherence assay, ERIC-PCR for phylogenetic analysis and whole genome sequencing of four highly drug resistant isolates. Out of the 117 isolates, 68.4% were positive for blaCTX-M, 39.3% for blaTEM, 30.8% for blaNDM-1, 13.7% for blaOXA and 1.7% for blaSHV gene. Upon screening for diarrheagenic genes, no isolates were found to harbour any of the tested genes. In the case of extraintestinal pathogenic E. coli (ExPEC) virulence factors, 7.6%, 11%, 5.9%, 4.3% and 21.2% of isolates harbored the focG, kpsMII, sfaS, afa and iutA genes, respectively. At a temperature of 25°C, 14.5% of isolates exhibited strong biofilm formation with 21.4% and 28.2% exhibiting moderate and weak biofilm formation respectively, whereas 35.9% were non-biofilm formers. On the other hand at 37°C, 2.6% of isolates showed strong biofilm formation with 3.4% and 31.6% showing moderate and weak biofilm formation respectively, whereas, 62.4% were non-biofilm formers. Regarding antibiotic susceptibility testing, all isolates were found to be multidrug-resistant (MDR), with 30 isolates being highly drug resistant. ERIC-PCR resulted in 12 clusters, with cluster E-10 containing the maximum number of isolates. Hierarchical clustering and correlation analysis revealed associations between environmental and clinical isolates, indicating likely transmission and dissemination from the hospital environment to the patients. The whole genome sequencing of four highly drug resistant ExPEC isolates showed the presence of various antimicrobial resistance genes, virulence factors and mobile genetic elements, with isolates harbouring the plasmid incompatibility group IncF (FII, FIB, FIA). The sequenced isolates were identified as human pathogens with a 93.3% average score. This study suggests that ESBL producing E. coli are prevalent in the healthcare settings of Bangladesh, acting as a potential reservoir for AMR bacteria. This information may have a profound effect on treatment, and improvements in public healthcare policies are a necessity to combat the increased incidences of hospital-acquired infections in the country.

Old and new aspects of influenza

Influenza is a classic infectious disease that, through the continuous variation of the viruses that produce it, imposes new challenges that we must solve as quickly as possible. The COVID-19 pandemic has substantially modified the behavior of influenza and other respiratory viruses, and in the coming years we will have to coexist with a new pathogen that will probably interact with existing pathogens in a way that we cannot yet glimpse. However, knowledge prior to the pandemic allows us to focus on the aspects that must be modified to make influenza an acceptable challenge for the future. In this review, emphasis is placed on the most relevant aspects of epidemiology, disease burden, diagnosis, and vaccine prevention, and how scientific and clinical trends in these aspects flow from the previously known to future challenges.

An Overview of Antimicrobial Resistance Profiles of Publicly Available Salmonella Genomes with Sufficient Quality and Metadata

Salmonella enterica (S. enterica) is a commensal organism or pathogen causing diseases in animals and humans, as well as widespread in the environment. Antimicrobial resistance (AMR) has increasingly affected both animal and human health and continues to raise public health concerns. A decade ago, it was estimated that the increased use of whole genome sequencing (WGS) combined with sharing of public data would drastically change and improve the surveillance and understanding of Salmonella epidemiology and AMR. This study aimed to evaluate the current usefulness of public WGS data for Salmonella surveillance and to investigate the associations between serovars, antibiotic resistance genes (ARGs), and metadata. Out of 191,306 Salmonella genomes deposited in European Nucleotide Archive and NCBI databases, 47,452 WGS with sufficient minimum metadata (country, year, and source) of S. enterica were retrieved from 116 countries and isolated between 1905 and 2020. For in silico analysis of the WGS data, KmerFinder, SISTR, and ResFinder were used for species, serovars, and AMR identification, respectively. The results showed that the five common isolation sources of S. enterica are human (29.10%), avian (22.50%), environment (11.89%), water (9.33%), and swine (6.62%). The most common ARG profiles for each class of antimicrobials are β-lactam (blaTEM-1B; 6.78%), fluoroquinolone [(parC[T57S], qnrB19); 0.87%], folate pathway antagonist (sul2; 8.35%), macrolide [mph(A); 0.39%], phenicol (floR; 5.94%), polymyxin B (mcr-1.1; 0.09%), and tetracycline [tet(A); 12.95%]. Our study reports the first overview of ARG profiles in publicly available Salmonella genomes from online databases. All data sets from this study can be searched at Microreact.

Comparing antimicrobial resistant genes and phenotypes across multiple sequencing platforms and assays for Enterobacterales clinical isolates

INTRODUCTION

Whole genome sequencing (WGS) of bacterial isolates can be used to identify antimicrobial resistance (AMR) genes. Previous studies have shown that genotype-based AMR has variable accuracy for predicting carbapenem resistance in carbapenem-resistant Enterobacterales (CRE); however, the majority of these studies used short-read platforms (e.g. Illumina) to generate sequence data. In this study, our objective was to determine whether Oxford Nanopore Technologies (ONT) long-read WGS would improve detection of carbapenem AMR genes with respect to short-read only WGS for nine clinical CRE samples. We measured the minimum inhibitory breakpoint (MIC) using two phenotype assays (MicroScan and ETEST) for six antibiotics, including two carbapenems (meropenem and ertapenem) and four non-carbapenems (gentamicin, ciprofloxacin, cefepime, and trimethoprim/sulfamethoxazole). We generated short-read data using the Illumina NextSeq and long-read data using the ONT MinION. Four assembly methods were compared: ONT-only assembly; ONT-only assembly plus short-read polish; ONT + short-read hybrid assembly plus short-read polish; short-read only assembly.

RESULTS

Consistent with previous studies, our results suggest that the hybrid assembly produced the highest quality results as measured by gene completeness and contig circularization. However, ONT-only methods had minimal impact on the detection of AMR genes and plasmids compared to short-read methods, although, notably, differences in gene copy number differed between methods. All four assembly methods showed identical presence/absence of the blaKPC-2 carbapenemase gene for all samples. The two phenotype assays showed 100% concordant results for the non-carbapenems, but only 65% concordance for the two carbapenems. The presence/absence of AMR genes was 100% concordant with AMR phenotypes for all four non-carbapenem drugs, although only 22%-50% sensitivity for the carbapenems.

CONCLUSIONS

Overall, these findings suggest that the lack of complete correspondence between CRE AMR genotype and phenotype for carbapenems, while concerning, is independent of sequencing platform/assembly method.

Genus-wide genomic characterization of Macrococcus: insights into evolution, population structure, and functional potential

Introduction

Macrococcus species have been isolated from a range of mammals and mammal-derived food products. While they are largely considered to be animal commensals, Macrococcus spp. can be opportunistic pathogens in both veterinary and human clinical settings. This study aimed to provide insight into the evolution, population structure, and functional potential of the Macrococcus genus, with an emphasis on antimicrobial resistance (AMR) and virulence potential.

Methods

All high-quality, publicly available Macrococcus genomes (n = 104, accessed 27 August 2022), plus six South African genomes sequenced here (two strains from bovine clinical mastitis cases and four strains from beef products), underwent taxonomic assignment (using four different approaches), AMR determinant detection (via AMRFinderPlus), and virulence factor detection (using DIAMOND and the core Virulence Factor Database).

Results

Overall, the 110 Macrococcus genomes were of animal commensal, veterinary clinical, food-associated (including food spoilage), and environmental origins; five genomes (4.5%) originated from human clinical cases. Notably, none of the taxonomic assignment methods produced identical results, highlighting the potential for Macrococcus species misidentifications. The most common predicted antimicrobial classes associated with AMR determinants identified across Macrococcus included macrolides, beta-lactams, and aminoglycosides (n = 81, 61, and 44 of 110 genomes; 73.6, 55.5, and 40.0%, respectively). Genes showing homology to Staphylococcus aureus exoenzyme aureolysin were detected across multiple species (using 90% coverage, n = 40 and 77 genomes harboring aureolysin-like genes at 60 and 40% amino acid [AA] identity, respectively). S. aureus Panton-Valentine leucocidin toxin-associated lukF-PV and lukS-PV homologs were identified in eight M. canis genomes (≥40% AA identity, >85% coverage). Using a method that delineates populations using recent gene flow (PopCOGenT), two species (M. caseolyticus and M. armenti) were composed of multiple within-species populations. Notably, M. armenti was partitioned into two populations, which differed in functional potential (e.g., one harbored beta-lactamase family, type II toxin-antitoxin system, and stress response proteins, while the other possessed a Type VII secretion system; PopCOGenT p < 0.05).

Discussion

Overall, this study leverages all publicly available Macrococcus genomes in addition to newly sequenced genomes from South Africa to identify genomic elements associated with AMR or virulence potential, which can be queried in future experiments.

Comparison of genomic diversity between single and pooled Staphylococcus aureus colonies isolated from human colonisation cultures

The most common approach to sampling the bacterial populations within an infected or colonised host is to sequence genomes from a single colony obtained from a culture plate. However, it is recognized that this method does not capture the genetic diversity in the population. An alternative is to sequence a mixture containing multiple colonies ("pool-seq"), but this has the disadvantage that it is a non-homogeneous sample, making it difficult to perform specific experiments. We compared differences in measures of genetic diversity between eight single-colony isolates (singles) and pool-seq on a set of 2286 S. aureus culture samples. The samples were obtained by swabbing three body sites on 85 human participants quarterly for a year, who initially presented with a methicillin-resistant S. aureus skin and soft-tissue infection (SSTI). We compared parameters such as sequence quality, contamination, allele frequency, nucleotide diversity and pangenome diversity in each pool to the corresponding singles. Comparing singles from the same culture plate, we found that 18% of sample collections contained mixtures of multiple Multilocus sequence types (MLSTs or STs). We showed that pool-seq data alone could predict the presence of multi-ST populations with 95% accuracy. We also showed that pool-seq could be used to estimate the number of polymorphic sites in the population. Additionally, we found that the pool may contain clinically relevant genes such as antimicrobial resistance markers that may be missed when only examining singles. These results highlight the potential advantage of analysing genome sequences of total populations obtained from clinical cultures rather than single colonies.

Bacterial DNA metabolism analysis by metagenomic next-generation sequencing (mNGS) after treatment of bloodstream infection

BACKGROUND

With the advent of metagenomic next-generation sequencing (mNGS), the time of DNA metabolism can be explored after bacteria be killed. In this study, we applied mNGS in investigation of the clearance profile of circulating bacteria DNA.

METHODS

All of the rabbits were injected with the inactivated Escherichia coli. Using mNGS, we analyzed serial samples of plasma collected from rabbits to detect clearance profile of circulating E. coli DNA.

RESULTS

In this study, we found that the of E. coli DNA could still be detected 6 h after injecting killed bacteria. The clearance half-lives associated with the 2 phases are 0.37 and 1.81 h. We also explored there is no correlation between the disease severity with the E. coli DNA reads in circulation.

CONCLUSIONS

After the bacteria were completely killed, their DNA could still be detected in the blood circulation. The metabolism of bacterial DNA in the circulation had two phases: fast and slow phases, and there were no correlations between the level of bacteria reads with the severity of patients' disease after the bacteria have been completely killed.

Bacterial Genomics and Epidemiology

Innovative technologies for Whole-Genome Sequencing (WGS) help to improve our understanding of the epidemiology and pathogenesis of bacterial infectious diseases and are becoming affordable for most microbiological laboratories [...].

The Swiss Pathogen Surveillance Platform - towards a nation-wide One Health data exchange platform for bacterial, viral and fungal genomics and associated metadata

The Swiss Pathogen Surveillance Platform (SPSP) is a shared secure surveillance platform between human and veterinary medicine, to also include environmental and foodborne isolates. It enables rapid and detailed transmission monitoring and outbreak surveillance of pathogens using whole genome sequencing data and associated metadata. It features controlled data access, complex dynamic queries, dedicated dashboards and automated data sharing with international repositories, providing actionable results for public health and the vision to improve societal well-being and health.

Rapid Lineage Assignment of Severe Acute Respiratory Syndrome Coronavirus 2 Cases through Automated Library Preparation, Sequencing, and Bioinformatic Analysis

The coronavirus disease 2019 (COVID-19) pandemic has provided a stage to illustrate that there is considerable value in obtaining rapid, whole-genome-based information about pathogens. This article describes the utility of a commercially available, automated severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) library preparation, genome sequencing, and a bioinformatics analysis pipeline to provide rapid, near-real-time SARS-CoV-2 variant description. This study evaluated the turnaround time, accuracy, and other quality-related parameters obtained from commercially available automated sequencing instrumentation, from analysis of continuous clinical samples obtained from January 1, 2021, to October 6, 2021. This analysis included a base-by-base assessment of sequencing accuracy at every position in the SARS-CoV-2 chromosome using two commercially available methods. Mean turnaround time, from the receipt of a specimen for SARS-CoV-2 testing to the availability of the results, with lineage assignment, was <3 days. Accuracy of sequencing by one method was 100%, although certain sites on the genome were found repeatedly to have been sequenced with varying degrees of read error rate.

GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification

Whole genome sequencing (WGS) of clinical bacterial isolates has the potential to transform the fields of diagnostics and public health. To realize this potential, bioinformatic software that reports identification results needs to be developed that meets the quality standards of a diagnostic test. We developed GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking) using k-mer based strategies for identification of bacteria based on WGS reads. GAMBIT incorporates this algorithm with a highly curated searchable database of 48,224 genomes. Herein, we describe validation of the scoring methodology, parameter robustness, establishment of confidence thresholds and the curation of the reference database. We assessed GAMBIT by way of validation studies when it was deployed as a laboratory-developed test in two public health laboratories. This method greatly reduces or eliminates false identifications which are often detrimental in a clinical setting.

A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis

Background

Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen guided by drug susceptibility test (DST) results. In most settings, DST information is not available or is limited to isoniazid and fluoroquinolones. Whole genome sequencing could more accurately guide individualized treatment as the full drug resistance profile is obtained with a single test. Whole genome sequencing has not reached its full potential for patient care, in part due to the complexity of translating a resistance profile into the most effective individualized regimen.

Methods

We developed a treatment recommender clinical decision support system (CDSS) and an accompanying web application for user-friendly recommendation of the optimal individualized treatment regimen to a clinician.

Results

Following expert stakeholder meetings and literature review, nine drug features and 14 treatment regimen features were identified and quantified. Using machine learning, a model was developed to predict the optimal treatment regimen based on a training set of 3895 treatment regimen-expert feedback pairs. The acceptability of the treatment recommender CDSS was assessed as part of a clinical trial and in a routine care setting. Within the clinical trial setting, all patients received the CDSS recommended treatment. In 8 of 20 cases, the initial recommendation was recomputed because of stock out, clinical contra-indication or toxicity. In routine care setting, physicians rejected the treatment recommendation in 7 out of 15 cases because it deviated from the national TB treatment guidelines. A survey indicated that the treatment recommender CDSS is easy to use and useful in clinical practice but requires digital infrastructure support and training.

Conclusions

Our findings suggest that global implementation of the novel treatment recommender CDSS holds the potential to improve treatment outcomes of rifampicin resistant tuberculosis.

WGS Data Collections: How Do Genomic Databases Transform Medicine?

As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and may play an important regulatory function. The first WGS-based datasets have already been released including underrepresented populations. Although many databases contain pooled data from several cohorts, recently the importance of local databases has been highlighted. Genomic databases are not only collecting data but may also contribute to better diagnostics and therapies. They may find applications in population studies, rare diseases, oncology, pharmacogenetics, and infectious and inflammatory diseases. Further data may be analysed with Al technologies and in the context of other omics data. To exemplify their utility, we put a highlight on the Polish genome database and its practical application.

Genomic Characteristics and Phylogenetic Analyses of a Multiple Drug-Resistant Klebsiella pneumoniae Harboring Plasmid-Mediated MCR-1 Isolated from Tai'an City, China

Klebsiella pneumoniae is a clinically common opportunistic pathogen that causes pneumonia and upper respiratory tract infection in humans as well as community-and hospital-acquired infections, posing significant threats to public health. Moreover, the insertion of a plasmid carrying the mobile colistin resistance (MCR) genes brings obstacles to the clinical treatment of K. pneumoniae infection. In this study, a strain of colistin-resistant K. pneumoniae (CRKP) was isolated from sputum samples of a patient who was admitted to a tertiary hospital in Tai'an city, China, and tested for drug sensitivity. The results showed that KPTA-2108 was multidrug-resistant (MDR), being resistant to 21 of 26 selected antibiotics, such as cefazolin, amikacin, tigecycline and colistin but sensitive to carbapenems via antibiotic resistance assays. The chromosome and plasmid sequences of the isolated strain KPTA-2108 were obtained using whole-genome sequencing technology and then were analyzed deeply using bioinformatics methods. The whole-genome sequencing analysis showed that the length of KPTA-2108 was 5,306,347 bp and carried four plasmids, pMJ4-1, pMJ4-2, pMJ4-3, and pMJ4-4-MCR. The plasmid pMJ4-4-MCR contained 30,124 bp and was found to be an IncX4 type. It was the smallest plasmid in the KPTA-2108 strain and carried only one resistance gene MCR-1. Successful conjugation tests demonstrated that pMJ4-4-MCR carrying MCR-1 could be horizontally transmitted through conjugation between bacteria. In conclusion, the acquisition and genome-wide characterization of a clinical MDR strain of CRKP may provide a scientific basis for the treatment of K. pneumoniae infection and epidemiological data for the surveillance of CRKP.

Fungal Whole-Genome Sequencing for Species Identification: From Test Development to Clinical Utilization

Using next-generation sequencing (NGS), we developed and validated a whole-genome sequencing (WGS)-based clinical test for fungal species identification on clinical isolates. The identification is mainly based on the fungal ribosomal internal transcribed spacer (ITS) region as the primary marker, and additional marker and genomic analysis applied for species within the Mucorales family (using the 28S rRNA gene) and Aspergillus genus (using the beta-tubulin gene and k-mer tree-based phylogenetic clustering). The validation study involving 74 unique fungal isolates (22 yeasts, 51 molds, and 1 mushroom-forming fungus) showed high accuracy, with 100% (74/74) concordance on the genus-level identifications and 89.2% (66/74) concordance on the species level. The 8 discrepant results were due to either the limitation of conventional morphology-based methodology or taxonomic changes. After one year of implementation in our clinical laboratory, this fungal NGS test was utilized in 29 cases; the majority of them were transplant and cancer patients. We demonstrated the utility of this test by detailing five case studies, in which accurate fungal species identification led to correct diagnosis, treatment adjustment or was ruled out for hospital acquired infection. This study provides a model for validation and implementation of WGS for fungal identification in a complex health system that serves a large immunocompromised patient population.

Genotypic resistance determined by whole genome sequencing versus phenotypic resistance in 234 Escherichia coli isolates

Whole genome sequencing (WGS) enables detailed characterization of bacteria at single nucleotide resolution. It provides data about acquired resistance genes and mutations leading to resistance. Although WGS is becoming an essential tool to predict resistance patterns accurately, comparing genotype to phenotype with WGS is still in its infancy. Additional data and validation are needed. In this retrospective study, we analysed 234 E. coli isolates from positive blood cultures using WGS as well as microdilution for 11 clinically relevant antibiotics, to compare the two techniques. We performed whole genome sequencing analyses on 234 blood culture isolates (genotype) to detect acquired antibiotic resistance. Minimal inhibitory concentrations (MIC) for E. coli were performed for amoxicillin, cefepime, cefotaxime, ceftazidime, meropenem, amoxicillin/clavulanic acid, piperacillin/tazobactam, amikacin, gentamicin, tobramycin, and ciprofloxacin, using the ISO 20776-1 standard broth microdilution method as recommended by EUCAST (phenotype). We then compared the two methods for statistical 'agreement'. A perfect (100%) categorical agreement between genotype and phenotype was observed for gentamicin and meropenem. However, no resistance to meropenem was observed. A high categorical agreement (> 95%) was observed for amoxicillin, cefepime, cefotaxime, ceftazidime, amikacin, and tobramycin. A categorical agreement lower than 95% was observed for amoxicillin/clavulanic acid, piperacillin/tazobactam, and ciprofloxacin. Most discrepancies occurred in isolates with MICs within ± 1 doubling dilution of the breakpoint and 22.73% of the major errors were samples that tested phenotypically susceptible at higher antibiotic exposure and were therefore considered as 'not resistant'. This study shows that WGS can be used as a valuable tool to predict phenotypic resistance against most of the clinically relevant antibiotics used for the treatment of E. coli bloodstream infections.

An ISO-certified genomics workflow for identification and surveillance of antimicrobial resistance

Realising the promise of genomics to revolutionise identification and surveillance of antimicrobial resistance (AMR) has been a long-standing challenge in clinical and public health microbiology. Here, we report the creation and validation of abritAMR, an ISO-certified bioinformatics platform for genomics-based bacterial AMR gene detection. The abritAMR platform utilises NCBI's AMRFinderPlus, as well as additional features that classify AMR determinants into antibiotic classes and provide customised reports. We validate abritAMR by comparing with PCR or reference genomes, representing 1500 different bacteria and 415 resistance alleles. In these analyses, abritAMR displays 99.9% accuracy, 97.9% sensitivity and 100% specificity. We also compared genomic predictions of phenotype for 864 Salmonella spp. against agar dilution results, showing 98.9% accuracy. The implementation of abritAMR in our institution has resulted in streamlined bioinformatics and reporting pathways, and has been readily updated and re-verified. The abritAMR tool and validation datasets are publicly available to assist laboratories everywhere harness the power of AMR genomics in professional practice.

A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia

Introduction

Microbial isolates from culture can be identified using 16S or whole-genome sequencing which generates substantial costs and requires time and expertise. Protein fingerprinting via Matrix-assisted Laser Desorption Ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used for rapid bacterial identification in routine diagnostics but shows a poor performance and resolution on commensal bacteria due to currently limited database entries. The aim of this study was to develop a MALDI-TOF MS plugin database (CLOSTRI-TOF) allowing for rapid identification of non-pathogenic human commensal gastrointestinal bacteria.

Methods

We constructed a database containing mass spectral profiles (MSP) from 142 bacterial strains representing 47 species and 21 genera within the class Clostridia. Each strain-specific MSP was constructed using >20 raw spectra measured on a microflex Biotyper system (Bruker-Daltonics) from two independent cultures.

Results

For validation, we used 58 sequence-confirmed strains and the CLOSTRI-TOF database successfully identified 98 and 93% of the strains, respectively, in two independent laboratories. Next, we applied the database to 326 isolates from stool of healthy Swiss volunteers and identified 264 (82%) of all isolates (compared to 170 (52.1%) with the Bruker-Daltonics library alone), thus classifying 60% of the formerly unknown isolates.

Discussion

We describe a new open-source MSP database for fast and accurate identification of the Clostridia class from the human gut microbiota. CLOSTRI-TOF expands the number of species which can be rapidly identified by MALDI-TOF MS.

An ST131 clade and a phylogroup A clade bearing an O101-like O-antigen cluster predominate among bloodstream Escherichia coli isolates from South-West Nigeria hospitals

Escherichia coli bloodstream infections are typically attributed to a limited number of lineages that carry virulence factors associated with invasiveness. In Nigeria, the identity of circulating clones is largely unknown and surveillance of their antimicrobial resistance has been limited. We verified and whole-genome sequenced 68 2016-2018 bloodstream E. coli isolates from three sentinel sites in South-Western Nigeria and susceptibility tested 67 of them. Resistance to antimicrobials commonly used in Nigeria was high, with 67 (100 %), 62 (92.5 %), 53 (79.1 %) and 37 (55.2 %) showing resistance to trimethoprim, ampicillin, ciprofloxacin and aminoglycosides, respectively. Thirty-five (51 %) isolates carried extended-spectrum β-lactamase genes and 32 (91 %) of these were multidrug resistant. All the isolates were susceptible to carbapenems and colistin. The strain set included globally disseminated high-risk clones from sequence type (ST)12 (2), ST131 (12) and ST648 (4). Twenty-three (33.8 %) of the isolates clustered within two clades. The first of these consisted of ST131 strains, comprising O16:H5 and O25:H4 sub-lineages. The second was an ST10-ST167 complex clade comprising strains carrying O-antigen and capsular genes of likely Klebsiella origin, identical to those of avian pathogenic E. coli Sanji, and serotyped in silico as O89, O101 or ONovel32, depending on the tool used. Four temporally associated ST90 strains from one sentinel were closely related enough to suggest that at least some of them represented a retrospectively detected outbreak cluster. Our data implicate a broad repertoire of E. coli isolates associated with bloodstream infections in South-West Nigeria. Continued genomic surveillance is valuable for tracking clones of importance and for outbreak identification.

A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data

The use of whole-genome sequencing (WGS) for bacterial characterisation has increased substantially in the last decade. Its high throughput and decreasing cost have led to significant changes in outbreak investigations and surveillance of a wide variety of microbial pathogens. Despite the innumerable advantages of WGS, several drawbacks concerning data analysis and management, as well as a general lack of standardisation, hinder its integration in routine use. In this work, a bioinformatics workflow for (Illumina) WGS data is presented for bacterial characterisation including genome annotation, species identification, serotype prediction, antimicrobial resistance prediction, virulence-related genes and plasmid replicon detection, core-genome-based or single nucleotide polymorphism (SNP)-based phylogenetic clustering and sequence typing. Workflow was tested using a collection of 22 in-house sequences of Salmonella enterica isolates belonging to a local outbreak, coupled with a collection of 182 Salmonella genomes publicly available. No errors were reported during the execution period, and all genomes were analysed. The bioinformatics workflow can be tailored to other pathogens of interest and is freely available for academic and non-profit use as an uploadable file to the Galaxy platform.

The value of next-generation sequencing for the diagnosis of Streptococcus suis meningitis

OBJECTIVE

The aim of this study was to investigate the value of next-generation sequencing for the diagnosis of Streptococcus suis meningitis.

METHODS

Patients with meningitis in the Department of Neurology of the Hainan General Hospital were recruited and divided into a next-generation sequencing group and a control group. In the next-generation sequencing group, we used the next-generation sequencing method to detect the specific pathogenic bacteria in the patients. In the control group, we used the cerebrospinal fluid bacterial culture method to detect the specific pathogenic bacteria in the patients.

RESULTS

A total of 28 participants were recruited for this study, with 14 participants in each group. The results showed similarities in both the average age and average course of the disease between the two groups (p>0.05). The white blood cell count, percentage of neutrophils, and level of C-reactive protein in the next-generation sequencing group were significantly higher than those in the control group (p<0.05). There were similarities in both the temperature and intracranial pressure between the two groups (p>0.05). In the next-generation sequencing group, all patients (100%) were detected as having had the S. suis meningitis infection by next-generation sequencing, while only 6 (43%) patients in the control group had been detected as having the S. suis meningitis infection by cerebrospinal fluid bacterial culture.

CONCLUSIONS

The positive detection rate of S. suis by the next-generation sequencing method was significantly higher compared with using a cerebrospinal fluid bacterial culture. Therefore, the next-generation sequencing method is valuable for the diagnosis of S. suis meningitis and is worthy of clinical application.

Aptamers: A prospective tool for infectious diseases diagnosis

It is well known that people's health is seriously threatened by various pathogens (such as Mycobacterium tuberculosis, Treponema pallidum, Novel coronavirus, HIV, Mucor, etc.), which leads to heavy socioeconomic burdens. Therefore, early and accurate pathogen diagnosis is essential for timely and effective therapies. Up to now, diagnosing human contagious diseases at molecule and nano levels is remarkably difficult owing to insufficient valid probes when it comes to determining the biological markers of pathogens. Aptamers are a set of high‐specificity and high‐sensitivity plastic oligonucleotides screened in vitro via the selective expansion of ligands by exponential enrichment (SELEX). With the advent of aptamer‐based technologies, their merits have aroused mounting academic interest. In recent years, as new detection and treatment tools, nucleic acid aptamers have been extensively utilized in the field of biomedicine, such as pathogen detection, new drug development, clinical diagnosis, nanotechnology, etc. However, the traditional SELEX method is cumbersome and has a long screening cycle, and it takes several months to screen out aptamers with high specificity. With the persistent development of SELEX‐based aptamer screening technologies, the application scenarios of aptamers have become more and more extensive. The present research briefly reviews the research progress of nucleic acid aptamers in the field of biomedicine, especially in the diagnosis of contagious diseases.

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.

Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

Metagenomic Next-Generation Sequencing Successfully Detects Pulmonary Infectious Pathogens in Children With Hematologic Malignancy

Background

Pulmonary infection is a leading cause of mortality in pediatric patients with hematologic malignancy (HM). In clinical settings, pulmonary pathogens are frequently undetectable, and empiric therapies may be costly, ineffective and lead to poor outcomes in this vulnerable population. Metagenomic next-generation sequencing (mNGS) enhances pathogen detection, but data on its application in pediatric patients with HM and pulmonary infections are scarce.

Methods

We retrospectively reviewed 55 pediatric patients with HM and pulmonary infection who were performed mNGS on bronchoalveolar lavage fluid from January 2020 to October 2021. The performances of mNGS methods and conventional microbiological methods in pathogenic diagnosis and subsequently antibiotic adjustment were investigated.

Results

A definite or probable microbial etiology of pulmonary infection was established for 50 of the 55 patients (90.9%) when mNGS was combined with conventional microbiological tests. The positive rate was 87.3% (48 of 55 patients) for mNGS versus 34.5% (19 of 55 patients) with conventional microbiological methods (P < 0.001). Bacteria, viruses and fungi were detected in 17/55 (30.9%), 25/55 (45.5%) and 19/55 (34.5%) cases using mNGS, respectively. Furthermore, 17 patients (30.9%) were identified as pulmonary mixed infections. Among the 50 pathogen-positive cases, 38% (19/50) were not completely pathogen-covered by empirical antibiotics and all of them were accordingly made an antibiotic adjustment. In the present study, the 30-day mortality rate was 7.3%.

Conclusion

mNGS is a valuable diagnostic tool to determine the etiology and appropriate treatment in pediatric patients with HM and pulmonary infection. In these vulnerable children with HM, pulmonary infections are life-threatening, so we recommend that mNGS should be considered as a front-line diagnostic test.

Alignment of Fellowship Training with Practice Patterns for Molecular Pathologists: A Report of the Association for Molecular Pathology Training and Education Committee

In the two decades since Accreditation Council for Graduate Medical Education-accredited Molecular Genetic Pathology fellowships began, the field of clinical molecular pathology has evolved considerably. The American Board of Pathology gathered data from board-certified molecular genetic pathologists assessing the alignment of skills and knowledge gained during fellowship with current needs on the job. The Association of Molecular Pathology conducted a parallel survey of program directors, and included questions on how various topics were taught during fellowship, as well as ranking their importance. Both surveys showed that most training aligned well with the practice needs of former trainees. Genomic profiling of tumors by next-generation sequencing, bioinformatics, laboratory management, and regulatory issues were topics thought to require increased emphasis in training. Topics related to clinical genetics and microbiology were deemed less important by those in practice, perhaps reflecting the increasing subspecialization of molecular pathologists. Program directors still viewed these topics as important to provide foundational knowledge. Parentage, identity, and human leukocyte antigen testing were less important to both survey audiences. These data may be helpful in guiding future adjustments to the Molecular Genetic Pathology curriculum and Accreditation Council for Graduate Medical Education program requirements.

Express Yourself: Quantitative Real-Time PCR Assays for Rapid Chromosomal Antimicrobial Resistance Detection in Pseudomonas aeruginosa

The rise of antimicrobial-resistant (AMR) bacteria is a global health emergency. One critical facet of tackling this epidemic is more rapid AMR diagnosis in serious multidrug-resistant pathogens like Pseudomonas aeruginosa. Here, we designed and then validated two multiplex quantitative real-time PCR (qPCR) assays to simultaneously detect differential expression of the resistance-nodulation-division efflux pumps MexAB-OprM, MexCD-OprJ, MexEF-OprN, and MexXY-OprM, the AmpC β-lactamase, and the porin OprD, which are commonly associated with chromosomally encoded AMR. Next, qPCRs were tested on 15 sputa from 11 participants with P. aeruginosa respiratory infections to determine AMR profiles in vivo. We confirmed multiplex qPCR testing feasibility directly on sputa, representing a key advancement in in vivo AMR diagnosis. Notably, comparison of sputa with their derived isolates grown in Luria-Bertani broth (±2.5% NaCl) or a 5-antibiotic cocktail showed marked expression differences, illustrating the difficulty in replicating in vivo expression profiles in vitro. Cystic fibrosis sputa showed significantly reduced mexE and mexY expression compared with chronic obstructive pulmonary disease sputa, despite harboring fluoroquinolone- and aminoglycoside-resistant strains, indicating that these loci do not contribute to AMR in vivo. oprD was also significantly downregulated in cystic fibrosis sputa, even in the absence of contemporaneous carbapenem use, suggesting a common adaptive trait in chronic infections that may affect carbapenem efficacy. Sputum ampC expression was highest in participants receiving carbapenems (6.7 to 15×), some of whom were simultaneously receiving cephalosporins, the latter of which would be rendered ineffective by the upregulated ampC. Our qPCR assays provide valuable insights into the P. aeruginosa resistome, and their use on clinical specimens will permit timely treatment alterations that will improve patient outcomes and antimicrobial stewardship measures.

A Hierarchical Genotyping Framework Using DNA Melting Temperatures Applied to Adenovirus Species Typing

Known genetic variation, in conjunction with post-PCR melting curve analysis, can be leveraged to provide increased taxonomic detail for pathogen identification in commercial molecular diagnostic tests. Increased taxonomic detail may be used by clinicians and public health decision-makers to observe circulation patterns, monitor for outbreaks, and inform testing practices. We propose a method for expanding the taxonomic resolution of PCR diagnostic systems by incorporating a priori knowledge of assay design and sequence information into a genotyping classification model. For multiplexed PCR systems, this framework is generalized to incorporate information from multiple assays to increase classification accuracy. An illustrative hierarchical classification model for human adenovirus (HAdV) species was developed and demonstrated ~95% cross-validated accuracy on a labeled dataset. The model was then applied to a near-real-time surveillance dataset in which deidentified adenovirus detected patient test data from 2018 through 2021 were classified into one of six adenovirus species. These results show a marked change in both the predicted prevalence for HAdV and the species makeup with the onset of the COVID-19 pandemic. HAdV-B decreased from a pre-pandemic predicted prevalence of up to 40% to less than 5% in 2021, while HAdV-A and HAdV-F species both increased in predicted prevalence.

Companion Animals—An Overlooked and Misdiagnosed Reservoir of Carbapenem Resistance

The dissemination of antimicrobial-resistance is a major global threat affecting both human and animal health. Carbapenems are human use β-lactams of last resort; thus. the dissemination of carbapenemase-producing (CP) bacteria creates severe limitations for the treatment of multidrug-resistant bacteria in hospitalized patients. Even though carbapenems are not routinely used in veterinary medicine, reports of infection or colonization by carbapenemase-producing Enterobacterales in companion animals are being reported. NDM-5 and OXA-48-like carbapenemases are among the most frequently reported in companion animals. Like in humans, Escherichia coli and Klebsiella pneumoniae are the most represented CP Enterobacterales found in companion animals, alongside with Acinetobacter baumannii. Considering that the detection of carbapenemase-producing Enterobacterales presents several difficulties, misdiagnosis of CP bacteria in companion animals may lead to important animal and public-health consequences. It is of the upmost importance to ensure an adequate monitoring and detection of CP bacteria in veterinary microbiology in order to safeguard animal health and minimise its dissemination to humans and the environment. This review encompasses an overview of the carbapenemase detection methods currently available, aiming to guide veterinary microbiologists on the best practices to improve its detection for clinical or research purposes.

Routine use of 16S rRNA PCR and subsequent sequencing from blood samples in septic shock: about two case reports of Capnocytophaga canimorsus infection in immunocompetent patients

Background

Capnocytophaga canimorsus infection happens frequently in immunosuppressed patients with reported domestic animal bites. Clinical presentation ranges from simple cellulitis to fulminant septic shock with disseminated intravascular coagulopathy, with an overall mortality of 30%. Conventional blood culture is often negative as this is a slow-growing pathogen. Nevertheless, the increasing use of 16S rRNA gene amplification and Sanger sequencing allows a much more rapid diagnostic confirmation. We present two case reports where 16S rRNA gene sequencing helped to diagnose Capnocytophaga canimorsus infection.

Case presentation

Case 1: A 53-year-old man with a history of non-cirrhotic chronic alcohol consumption was admitted to the intensive care unit (ICU) for septic shock and disseminated intravascular coagulopathy (DIC) of unknown origin. Blood cultures remained negative and a 16S rRNA PCR was performed leading to the identification of Capnocytophaga Canimorsus on day 4. Targeted antibiotic therapy with ceftriaxone for 14 days lead to overall recovery. Afterwards, the patient recalled a dog bite 2 days before hospitalization with a punctiform necrotic wound localized on a finger, which was not obvious at admission. Case 2: A 38-year-old man arrived to the emergency department for acute alcohol intoxication and history of a dog bite 2 days before. At admission, septic shock with purpura fulminans was diagnosed and required ICU hospitalization, invasive mechanical ventilation, vasopressor support and renal replacement therapy due to the rapid clinical deterioration. In the context of septic shock with purpura fulminans, DIC and recent dog bite, the diagnosis of Capnocytophaga canimorsus septic shock was suspected, and early confirmed by 16S rRNA PCR coupled to Sanger sequencing on day 2. Blood cultures became only positive for Capnocytophaga canimorsus 5 days after admission. Ceftriaxone alone was infused for 10 days in total, and the patient was discharged from the ICU on day 25.

Conclusions

16S rRNA gene PCR proves an important diagnostic tool when facing a sepsis of unknown origin. In these two cases of septic shock related to Capnocytophaga canimorsus, initial blood cultures remained negative at 24 h, whereas the diagnosis was achieved by 16S rRNA PCR sequencing performed from blood samples obtained at admission.

Metagenomic Next-Generation Sequencing for the Diagnosis of Suspected Opportunistic Infections in People Living with HIV

Objective

The diagnosis of suspected opportunistic infections in HIV patients is challenging due to the wide range of potential causes. This study used mNGS to analyse specimens of suspected opportunistic infections in HIV patients from a single centre to explore this method’s applicability as a diagnostic tool compared to that of CMTs.

Methods

We retrospectively investigated 46 suspected opportunistic infections in people living with HIV(PLWH) Hospitalized at Hangzhou Xixi hospital from January 2020 to August 2021. In total, we collected 49 samples (3 patients provided 2 samples) and sent them out for mNGS.

Results

mNGS had a better detection rate for fungi and nontuberculous mycobacteria than that of CMTs. Specifically, the diagnostic detection rate of fungi (11 vs 19, P<0.05) and nontuberculous mycobacteria (1 vs 6, p<0.05) was significantly higher; there was no difference in detection rate for other pathogens (bacteria, Mycobacterium tuberculosis, or viruses). The sensitivity of mNGS was 90.91%, 50%, 0%, 100%, and 100% for detecting fungi, bacteria, Mycobacterium tuberculosis, nontuberculous mycobacteria, and viruses, respectively; the corresponding specificities were 74.29%, 97.73%, 86.36%, 86.67%, and 91.11%.

Conclusion

mNGS technology provides an alternative and promising method of identifying suspected opportunistic infections in PLWH. Thus, the best diagnosis strategy may be using a combination of mNGS and CMTs.

Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods

Antimicrobial resistance (AMR) has emerged as a major threat to public health globally. Accurate and rapid detection of resistance to antimicrobial drugs, and subsequent appropriate antimicrobial treatment, combined with antimicrobial stewardship, are essential for controlling the emergence and spread of AMR. This article reviews common antimicrobial susceptibility testing (AST) methods and relevant issues concerning the advantages and disadvantages of each method. Although accurate, classic technologies used in clinical microbiology to profile antimicrobial susceptibility are time-consuming and relatively expensive. As a result, physicians often prescribe empirical antimicrobial therapies and broad-spectrum antibiotics. Although recently developed AST systems have shown advantages over traditional methods in terms of testing speed and the potential for providing a deeper insight into resistance mechanisms, extensive validation is required to translate these methodologies to clinical practice. With a continuous increase in antimicrobial resistance, additional efforts are needed to develop innovative, rapid, accurate, and portable diagnostic tools for AST. The wide implementation of novel devices would enable the identification of the optimal treatment approaches and the surveillance of antibiotic resistance in health, agriculture, and the environment, allowing monitoring and better tackling the emergence of AMR.

A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.