Next-generation sequencing technologies and their application to the study and control of bacterial infections

Antimicrobial susceptibility and resistome of Actinobacillus pleuropneumoniae in Taiwan: a next-generation sequencing analysis

Actinobacillus pleuropneumoniae infection causes a high mortality rate in porcine animals. Antimicrobial resistance poses global threats to public health. The current study aimed to determine the antimicrobial susceptibilities and probe the resistome of A. pleuropneumoniae in Taiwan. Herein, 133 isolates were retrospectively collected; upon initial screening, 38 samples were subjected to next-generation sequencing (NGS). Over the period 2017-2022, the lowest frequencies of resistant isolates were found for ceftiofur, cephalexin, cephalothin, and enrofloxacin, while the highest frequencies of resistant isolates were found for oxytetracycline, streptomycin, doxycycline, ampicillin, amoxicillin, kanamycin, and florfenicol. Furthermore, most isolates (71.4%) showed multiple drug resistance. NGS-based resistome analysis revealed aminoglycoside- and tetracycline-related genes at the highest prevalence, followed by genes related to beta-lactam, sulfamethoxazole, florphenicol, and macrolide. A plasmid replicon (repUS47) and insertion sequences (IS10R and ISVAp11) were identified in resistant isolates. Notably, the multiple resistance roles of the insertion sequence IS10R were widely proposed in human medicine; however, this is the first time IS10R has been reported in veterinary medicine. Concordance analysis revealed a high consistency of phenotypic and genotypic susceptibility to florphenicol, tilmicosin, doxycycline, and oxytetracycline. The current study reports the antimicrobial characterization of A. pleuropneumoniae for the first time in Taiwan using NGS.

Comparison of plasma and blood cell samples in metagenomic next-generation sequencing for identification of the causative pathogens of fever

Background

Metagenomic next-generation sequencing (mNGS) of plasma DNA has become an attractive diagnostic method for infectious diseases; however, the rate of false-positive results is high. This study aims to evaluate the diagnostic accuracy of mNGS in plasma versus blood cell samples for immunocompromised children with febrile diseases.

Methods

The results of conventional microbiological test (CMT) and mNGS using plasma and blood cells in 106 patients with 128 episodes of febrile diseases from the Department of Hematology/Oncology were analyzed and described.

Results

The positivity rates for CMT and mNGS of plasma and blood cells were 35.9 %, 84.4 % and 46.9 %, respectively (P < 0.001). Notably, mNGS identified multiple pathogens in a single specimen in 68.5 % of plasma samples and 38.3 % of blood cell samples (P < 0.001). Furthermore, plasma and blood cell mNGS identified causative pathogens in 58 and 46 cases, accounting for 53.7 % and 76.7 % of the mNGS-positive cases for each sample type, respectively (P = 0.002). By integrating results from both plasma and blood cell samples, causative pathogens were identified in 77 cases (60.2 %), enhancing sensitivity to 87.5 % but reducing specificity to 15.0 %, compared to plasma (65.9 % sensitivity and 20.0 % specificity) and blood cell samples (52.3 % sensitivity and 80.0 % specificity).

Conclusions

mNGS of plasma is sensitive but has a high false-positive rate, while mNGS of blood cells has low sensitivity but higher specificity.

Complete circular assembly of Histophilus somni PDS1537697-81-1 genome and phenotypic characterization of its antibiotic susceptibility

A Histophilus somni isolate from a clinically healthy, fall-placed calf was obtained upon arrival to a commercial feedlot. Fall-placed calves are commonly viewed to be at high risk for the development of bovine respiratory disease. The isolate was phenotyped for antimicrobial susceptibility and sequenced to obtain a complete, circular, genome assembly.

Occurrence and genomic characterization of antimicrobial-resistant and potential pathogenic Escherichia coli from Italian artisanal food productions of animal origin

Escherichia coli can harbor a broad repertoire of virulence and antimicrobial resistance (AMR) genes, which can be exchanged across the human gastrointestinal microflora, thus posing a public health risk. In this study, 6 batches of artisanal soft cheese and a 6-month ripened fermented dried sausage were investigated to assess the occurrence, phylogeny, and genomic traits (AMR, virulence, and mobilome) of E. coli. 30 and 3 strains isolated from salami and cheese food chains, respectively, were confirmed as E. coli by whole genome sequencing. The accumulation of single nucleotide polymorphism differences within small clusters of strains encompassing batches or processing stages, combined with high serotype and phylogroup diversity, suggested the occurrence of different contamination phenomena among the facilities. A total of 8 isolates harbored plasmid-mediated resistance genes, including one cheese strain that carried an IncQ1 plasmid carrying AMR determinants to macrolides [mph(B)], sulfonamides (sul1, sul2), trimethoprim (dfrA1), and aminoglycosides [aph(3")-Ib and aph(6)-Id]. A pool of virulence-associated genes in the class of adhesion, colonization, iron uptake, and toxins, putative ColV-positive iron uptake systems sit, iro, or iuc (8 salami and 2 cheese), plasmid-encoded hemolysin operon hlyABCD (one salami), and potential atypical enteropathogenic E. coli (3 salami environment) were reported. Overall, our findings underscore the importance of routine surveillance of E. coli in the artisanal food chain to prevent the dissemination of AMR and virulence.

Omics technology draws a comprehensive heavy metal resistance strategy in bacteria

The rapid industrial revolution significantly increased heavy metal pollution, becoming a major global environmental concern. This pollution is considered as one of the most harmful and toxic threats to all environmental components (air, soil, water, animals, and plants until reaching to human). Therefore, scientists try to find a promising and eco-friendly technique to solve this problem i.e., bacterial bioremediation. Various heavy metal resistance mechanisms were reported. Omics technologies can significantly improve our understanding of heavy metal resistant bacteria and their communities. They are a potent tool for investigating the adaptation processes of microbes in severe conditions. These omics methods provide unique benefits for investigating metabolic alterations, microbial diversity, and mechanisms of resistance of individual strains or communities to harsh conditions. Starting with genome sequencing which provides us with complete and comprehensive insight into the resistance mechanism of heavy metal resistant bacteria. Moreover, genome sequencing facilitates the opportunities to identify specific metal resistance genes, operons, and regulatory elements in the genomes of individual bacteria, understand the genetic mechanisms and variations responsible for heavy metal resistance within and between bacterial species in addition to the transcriptome, proteome that obtain the real expressed genes. Moreover, at the community level, metagenome, meta transcriptome and meta proteome participate in understanding the microbial interactive network potentially novel metabolic pathways, enzymes and gene species can all be found using these methods. This review presents the state of the art and anticipated developments in the use of omics technologies in the investigation of microbes used for heavy metal bioremediation.

Legionella pneumophila exploits the endo-lysosomal network for phagosome biogenesis by co-opting SUMOylated Rab7

Legionella pneumophila strains harboring wild-type rpsL such as Lp02rpsLWT cannot replicate in mouse bone marrow-derived macrophages (BMDMs) due to induction of extensive lysosome damage and apoptosis. The bacterial factor directly responsible for inducing such cell death and the host factor involved in initiating the signaling cascade that leads to lysosome damage remain unknown. Similarly, host factors that may alleviate cell death induced by these bacterial strains have not yet been investigated. Using a genome-wide CRISPR/Cas9 screening, we identified Hmg20a and Nol9 as host factors important for restricting strain Lp02rpsLWT in BMDMs. Depletion of Hmg20a protects macrophages from infection-induced lysosomal damage and apoptosis, allowing productive bacterial replication. The restriction imposed by Hmg20a was mediated by repressing the expression of several endo-lysosomal proteins, including the small GTPase Rab7. We found that SUMOylated Rab7 is recruited to the bacterial phagosome via SulF, a Dot/Icm effector that harbors a SUMO-interacting motif (SIM). Moreover, overexpression of Rab7 rescues intracellular growth of strain Lp02rpsLWT in BMDMs. Our results establish that L. pneumophila exploits the lysosomal network for the biogenesis of its phagosome in BMDMs.

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Illumina and Nanopore sequencing in culture-negative samples from suspected lower respiratory tract infection patients

Objective

To evaluate the diagnostic value of metagenomic sequencing technology based on Illumina and Nanopore sequencing platforms for patients with suspected lower respiratory tract infection whose pathogen could not be identified by conventional microbiological tests.

Methods

Patients admitted to the Respiratory and Critical Care Medicine in Shanghai Ruijin Hospital were retrospectively studied from August 2021 to March 2022. Alveolar lavage or sputum was retained in patients with clinically suspected lower respiratory tract infection who were negative in conventional tests. Bronchoalveolar lavage fluid (BALF) samples were obtained using bronchoscopy. Sputum samples were collected, while BALF samples were not available due to bronchoscopy contraindications. Samples collected from enrolled patients were simultaneously sent for metagenomic sequencing on both platforms.

Results

Thirty-eight patients with suspected LRTI were enrolled in this study, consisting of 36 parts of alveolar lavage and 2 parts of sputum. According to the infection diagnosis, 31 patients were confirmed to be infected with pathogens, while 7 patients were diagnosed with non-infectious disease. With regard to the diagnosis of infectious diseases, the sensitivity and specificity of Illumina and Nanopore to diagnose infection in patients were 80.6% vs. 93.5% and 42.9 vs. 28.6%, respectively. In patients diagnosed with bacterial, Mycobacterium, and fungal infections, the positive rates of Illumina and Nanopore sequencer were 71.4% vs. 78.6%, 36.4% vs. 90.9%, and 50% vs. 62.5%, respectively. In terms of pathogen diagnosis, the sensitivity and specificity of pathogens detected by Illumina and Nanopore were 55.6% vs. 77.8% and 42.9% vs. 28.6%, respectively. Among the patients treated with antibiotics in the last 2 weeks, 61.1% (11/18) and 77.8% (14/18) cases of pathogens were accurately detected by Illumina and Nanopore, respectively, among which 8 cases were detected jointly. The consistency between Illumina and diagnosis was 63.9% (23/36), while the consistency between Nanopore and diagnosis was 83.3% (30/36). Between Illumina and Nanopore sequencing methods, the consistency ratio was 55% (22/42) based on pathogen diagnosis.

Conclusion

Both platforms play a certain value in infection diagnosis and pathogen diagnosis of CMT-negative suspected LRTI patients, providing a theoretical basis for clinical accurate diagnosis and symptomatic treatment. The Nanopore platform demonstrated potential advantages in the identification of Mycobacterium and could further provide another powerful approach for patients with suspected Mycobacterium infection.

Comparative whole genome analysis of face-derived Streptococcus infantis CX-4 unravels the functions related to skin barrier

BACKGROUND

The skin microbiome is essential in guarding against harmful pathogens and responding to environmental changes by generating substances useful in the cosmetic and pharmaceutical industries. Among these microorganisms, Streptococcus is a bacterial species identified in various isolation sources. In 2021, a strain of Streptococcus infantis, CX-4, was identified from facial skin and found to be linked to skin structure and elasticity. As the skin-derived strain differs from other S. infantis strains, which are usually of oral origin, it emphasizes the significance of bacterial variation by the environment.

OBJECTIVE

This study aims to explore the unique characteristics of the CX-4 compared to seven oral-derived Streptococcus strains based on the Whole-Genome Sequencing data, focusing on its potential role in skin health and its possible application in cosmetic strategies.

METHODS

The genome of the CX-4 strain was constructed using PacBio Sequencing, with the assembly performed using the SMRT protocol. Comparative whole-genome analysis was then performed with seven closely related strains, utilizing web-based tools like PATRIC, OrthoVenn3, and EggNOG-mapper, for various analyses, including protein association analysis using STRING.

RESULTS

Our analysis unveiled a substantial number of Clusters of Orthologous Groups in diverse functional categories in CX-4, among which sphingosine kinase (SphK) emerged as a unique product, exclusively present in the CX-4 strain. SphK is a critical enzyme in the sphingolipid metabolic pathway, generating sphingosine-1-phosphate. The study also brought potential associations with isoprene formation and retinoic acid synthesis, the latter being a metabolite of vitamin A, renowned for its crucial function in promoting skin cell growth, differentiation, and maintaining of skin barrier integrity. These findings collectively suggest the potential of the CX-4 strain in enhancing of skin barrier functionality.

CONCLUSION

Our research underscores the potential of the skin-derived S. infantis CX-4 strain by revealing unique bacterial compounds and their potential roles on human skin.

Genomic revisitation and reclassification of the genus Providencia

Members of Providencia, although typically opportunistic, can cause severe infections in immunocompromised hosts. Recent advances in genome sequencing provide an opportunity for more precise study of this genus. In this study, we first identified and characterized a novel species named Providencia zhijiangensis sp. nov. It has ≤88.23% average nucleotide identity (ANI) and ≤31.8% in silico DNA-DNA hybridization (dDDH) values with all known Providencia species, which fall significantly below the species-defining thresholds. Interestingly, we found that Providencia stuartii and Providencia thailandensis actually fall under the same species, evidenced by an ANI of 98.59% and a dDDH value of 90.4%. By fusing ANI with phylogeny, we have reclassified 545 genomes within this genus into 20 species, including seven unnamed taxa (provisionally titled Taxon 1-7), which can be further subdivided into 23 lineages. Pangenomic analysis identified 1,550 genus-core genes in Providencia, with coenzymes being the predominant category at 10.56%, suggesting significant intermediate metabolism activity. Resistance analysis revealed that most lineages of the genus (82.61%, 19/23) carry a high number of antibiotic-resistance genes (ARGs) and display diverse resistance profiles. Notably, the majority of ARGs are located on plasmids, underscoring the significant role of plasmids in the resistance evolution within this genus. Three species or lineages (P. stuartii, Taxon 3, and Providencia hangzhouensis L12) that possess the highest number of carbapenem-resistance genes suggest their potential influence on clinical treatment. These findings underscore the need for continued surveillance and study of this genus, particularly due to their role in harboring antibiotic-resistance genes.

IMPORTANCE

The Providencia genus, known to harbor opportunistic pathogens, has been a subject of interest due to its potential to cause severe infections, particularly in vulnerable individuals. Our research offers groundbreaking insights into this genus, unveiling a novel species, Providencia zhijiangensis sp. nov., and highlighting the need for a re-evaluation of existing classifications. Our comprehensive genomic assessment offers a detailed classification of 545 genomes into distinct species and lineages, revealing the rich biodiversity and intricate species diversity within the genus. The substantial presence of antibiotic-resistance genes in the Providencia genus underscores potential challenges for public health and clinical treatments. Our study highlights the pressing need for increased surveillance and research, enriching our understanding of antibiotic resistance in this realm.

Whole Genome Sequencing: Applications in Clinical Bacteriology

The success in determining the whole genome sequence of a bacterial pathogen was first achieved in 1995 by determining the complete nucleotide sequence of Haemophilus influenzae Rd using the chain-termination method established by Sanger et al. in 1977 and automated by Hood et al. in 1987. However, this technology was laborious, costly, and time-consuming. Since 2004, high-throughput next-generation sequencing technologies have been developed, which are highly efficient, require less time, and are cost-effective for whole genome sequencing (WGS) of all organisms, including bacterial pathogens. In recent years, the data obtained using WGS technologies coupled with bioinformatics analyses of the sequenced genomes have been projected to revolutionize clinical bacteriology. WGS technologies have been used in the identification of bacterial species, strains, and genotypes from cultured organisms and directly from clinical specimens. WGS has also helped in determining resistance to antibiotics by the detection of antimicrobial resistance genes and point mutations. Furthermore, WGS data have helped in the epidemiological tracking and surveillance of pathogenic bacteria in healthcare settings as well as in communities. This review focuses on the applications of WGS in clinical bacteriology.

Genome-based assessment of antimicrobial resistance reveals the lineage specificity of resistance and resistance gene profiles in Riemerella anatipestifer from China

Riemerella anatipestifer (R. anatipestifer) is an important pathogen that causes severe systemic infections in domestic ducks, resulting in substantial economic losses for China's waterfowl industry. Controlling R. anatipestifer with antibiotics is extremely challenging due to its multidrug resistance. Notably, large-scale studies on antimicrobial resistance (AMR) and the corresponding genetic determinants in R. anatipestifer remain scarce. To solve this dilemma, more than 400 nonredundant R. anatipestifer isolates collected from 22 provinces in China between 1994 and 2021 were subjected to broth dilution antibiotic susceptibility assays, and their resistance-associated genetic determinants were characterized by whole-genome sequencing. While over 90% of the isolates was resistant to sulfamethoxazole, kanamycin, gentamicin, ofloxacin, norfloxacin, and trimethoprim, 88.48% of the isolates was resistant to the last-resort drug (tigecycline). Notably, R. anatipestifer resistance to oxacillin, norfloxacin, ofloxacin, and tetracycline was found to increase relatively over time. Genome-wide analysis revealed the alarmingly high prevalence of blaOXA-like (93.05%) and tet(X) (90.64%) genes and the uneven distribution of resistance genes among lineages. Overall, this study reveals a serious AMR situation regarding R. anatipestifer in China, with a high prevalence and high diversity of antimicrobial resistance genes, providing important data for the rational use of antibiotics in veterinary practice.IMPORTANCERiemerella anatipestifer (R. anatipestifer), an important waterfowl pathogen, has caused substantial economic losses worldwide, especially in China. Antimicrobial resistance (AMR) is a major challenge in controlling this pathogen. Although a few studies have reported antimicrobial resistance in R. anatipestifer, comprehensive data remain a gap. This study aims to address the lack of information on R. anatipestifer AMR and its genetic basis. By analyzing more than 400 isolates collected over two decades, this study reveals alarming levels of resistance to several antibiotics, including drugs of last resort. The study also revealed the lineage-specificity of resistance profiles and resistance gene profiles. Overall, this study provides new insights and updated data support for understanding AMR and its genetic determinants in R. anatipestifer.

Revealing the seed microbiome: Navigating sequencing tools, microbial assembly, and functions to amplify plant fitness

Microbial communities within seeds play a vital role in transmitting themselves to the next generation of plants. These microorganisms significantly impact seed vigor and early seedling growth, for successful crop establishment. Previous studies reported on seed-associated microbial communities and their influence on processes like dormancy release, germination, and disease protection. Modern sequencing and conventional methods reveal microbial community structures and environmental impacts, these information helps in microbial selection and manipulation. These studies form the foundation for using seed microbiomes to enhance crop resilience and productivity. While existing research has primarily focused on characterizing microbiota in dried mature seeds, a significant gap exists in understanding how these microbial communities assemble during seed development. The review also discusses applying seed-associated microorganisms to improve crops in the context of climate change. However, limited knowledge is available about the microbial assembly pattern on seeds, and their impact on plant growth. The review provides insight into microbial composition, functions, and significance for plant health, particularly regarding growth promotion and pest control.

Antimicrobial resistance in multistate outbreaks of nontyphoidal Salmonella infections linked to animal contact-United States, 2015-2018

Animal contact is an established risk factor for nontyphoidal Salmonella infections and outbreaks. During 2015-2018, the U.S. Centers for Disease Control and Prevention (CDC) and other U.S. public health laboratories began implementing whole-genome sequencing (WGS) of Salmonella isolates. WGS was used to supplement the traditional methods of pulsed-field gel electrophoresis for isolate subtyping, outbreak detection, and antimicrobial susceptibility testing (AST) for the detection of resistance. We characterized the epidemiology and antimicrobial resistance (AMR) of multistate salmonellosis outbreaks linked to animal contact during this time period. An isolate was considered resistant if AST yielded a resistant (or intermediate, for ciprofloxacin) interpretation to any antimicrobial tested by the CDC or if WGS showed a resistance determinant in its genome for one of these agents. We identified 31 outbreaks linked to contact with poultry (n = 23), reptiles (n = 6), dairy calves (n = 1), and guinea pigs (n = 1). Of the 26 outbreaks with resistance data available, we identified antimicrobial resistance in at least one isolate from 20 outbreaks (77%). Of 1,309 isolates with resistance information, 247 (19%) were resistant to ≥1 antimicrobial, and 134 (10%) were multidrug-resistant to antimicrobials from ≥3 antimicrobial classes. The use of resistance data predicted from WGS increased the number of isolates with resistance information available fivefold compared with AST, and 28 of 43 total resistance patterns were identified exclusively by WGS; concordance was high (>99%) for resistance determined by AST and WGS. The use of predicted resistance from WGS enhanced the characterization of the resistance profiles of outbreaks linked to animal contact by providing resistance information for more isolates.

The important lessons lurking in the history of meningococcal epidemiology

INTRODUCTION

The epidemiology of invasive meningococcal disease (IMD), a rare but potentially fatal illness, is typically described as unpredictable and subject to sporadic outbreaks.

AREAS COVERED

Meningococcal epidemiology and vaccine use during the last ~ 200 years are examined within the context of meningococcal characterization and classification to guide future IMD prevention efforts.

EXPERT OPINION

Historical and contemporary data highlight the dynamic nature of meningococcal epidemiology, with continued emergence of hyperinvasive clones and affected regions. Recent shifts include global increases in serogroup W disease, meningococcal antimicrobial resistance (AMR), and meningococcal urethritis; additionally, unvaccinated populations have experienced disease resurgences following lifting of COVID-19 restrictions. Despite these changes, a close analysis of meningococcal epidemiology indicates consistent dominance of serogroups A, B, C, W, and Y and elevated IMD rates among infants and young children, adolescents/young adults, and older adults. Demonstrably effective vaccines against all 5 major disease-causing serogroups are available, and their prophylactic use represents a powerful weapon against IMD, including AMR. The World Health Organization's goal of defeating meningitis by the year 2030 demands broad protection against IMD, which in turn indicates an urgent need to expand meningococcal vaccination programs across major disease-causing serogroups and age-related risk groups.

Advanced design and applications of digital microfluidics in biomedical fields: An update of recent progress

Significant breakthroughs have been made in digital microfluidic (DMF)-based technologies over the past decades. DMF technology has attracted great interest in bioassays depending on automatic microscale liquid manipulations and complicated multi-step processing. In this review, the recent advances of DMF platforms in the biomedical field were summarized, focusing on the integrated design and applications of the DMF system. Firstly, the electrowetting-on-dielectric principle, fabrication of DMF chips, and commercialization of the DMF system were elaborated. Then, the updated droplets and magnetic beads manipulation strategies with DMF were explored. DMF-based biomedical applications were comprehensively discussed, including automated sample preparation strategies, immunoassays, molecular diagnosis, blood processing/testing, and microbe analysis. Emerging applications such as enzyme activity assessment and DNA storage were also explored. The performance of each bioassay was compared and discussed, providing insight into the novel design and applications of the DMF technology. Finally, the advantages, challenges, and future trends of DMF systems were systematically summarized, demonstrating new perspectives on the extensive applications of DMF in basic research and commercialization.

Rapid identification of enteric bacteria from whole genome sequences using average nucleotide identity metrics

Identification of enteric bacteria species by whole genome sequence (WGS) analysis requires a rapid and an easily standardized approach. We leveraged the principles of average nucleotide identity using MUMmer (ANIm) software, which calculates the percent bases aligned between two bacterial genomes and their corresponding ANI values, to set threshold values for determining species consistent with the conventional identification methods of known species. The performance of species identification was evaluated using two datasets: the Reference Genome Dataset v2 (RGDv2), consisting of 43 enteric genome assemblies representing 32 species, and the Test Genome Dataset (TGDv1), comprising 454 genome assemblies which is designed to represent all species needed to query for identification, as well as rare and closely related species. The RGDv2 contains six Campylobacter spp., three Escherichia/Shigella spp., one Grimontia hollisae, six Listeria spp., one Photobacterium damselae, two Salmonella spp., and thirteen Vibrio spp., while the TGDv1 contains 454 enteric bacterial genomes representing 42 different species. The analysis showed that, when a standard minimum of 70% genome bases alignment existed, the ANI threshold values determined for these species were ≥95 for Escherichia/Shigella and Vibrio species, ≥93% for Salmonella species, and ≥92% for Campylobacter and Listeria species. Using these metrics, the RGDv2 accurately classified all validation strains in TGDv1 at the species level, which is consistent with the classification based on previous gold standard methods.

Exploring microbial worlds: a review of whole genome sequencing and its application in characterizing the microbial communities

The classical microbiology techniques have inherent limitations in unraveling the complexity of microbial communities, necessitating the pivotal role of sequencing in studying the diversity of microbial communities. Whole genome sequencing (WGS) enables researchers to uncover the metabolic capabilities of the microbial community, providing valuable insights into the microbiome. Herein, we present an overview of the rapid advancements achieved thus far in the use of WGS in microbiome research. There was an upsurge in publications, particularly in 2021 and 2022 with the United States, China, and India leading the metagenomics research landscape. The Illumina platform has emerged as the widely adopted sequencing technology, whereas a significant focus of metagenomics has been on understanding the relationship between the gut microbiome and human health where distinct bacterial species have been linked to various diseases. Additionally, studies have explored the impact of human activities on microbial communities, including the potential spread of pathogenic bacteria and antimicrobial resistance genes in different ecosystems. Furthermore, WGS is used in investigating the microbiome of various animal species and plant tissues such as the rhizosphere microbiome. Overall, this review reflects the importance of WGS in metagenomics studies and underscores its remarkable power in illuminating the variety and intricacy of the microbiome in different environments.

Effectiveness of Self-Collected, Ambient Temperature-Preserved Nasal Swabs Compared to Samples Collected by Trained Staff for Genotyping of Respiratory Viruses by Shotgun RNA Sequencing: Comparative Study

BACKGROUND

The SARS-CoV-2 pandemic has underscored the need for field specimen collection and transport to diagnostic and public health laboratories. Self-collected nasal swabs transported without dependency on a cold chain have the potential to remove critical barriers to testing, expand testing capacity, and reduce opportunities for exposure of health professionals in the context of a pandemic.

OBJECTIVE

We compared nasal swab collection by study participants from themselves and their children at home to collection by trained research staff.

METHODS

Each adult participant collected 1 nasal swab, sampling both nares with the single swab, after which they collected 1 nasal swab from 1 child. After all the participant samples were collected for the household, the research staff member collected a separate single duplicate sample from each individual. Immediately after the sample collection, the adult participants completed a questionnaire about the acceptability of the sampling procedures. Swabs were placed in temperature-stable preservative and respiratory viruses were detected by shotgun RNA sequencing, enabling viral genome analysis.

RESULTS

In total, 21 households participated in the study, each with 1 adult and 1 child, yielding 42 individuals with paired samples. Study participants reported that self-collection was acceptable. Agreement between identified respiratory viruses in both swabs by RNA sequencing demonstrated that adequate collection technique was achieved by brief instructions.

CONCLUSIONS

Our results support the feasibility of a scalable and convenient means for the identification of respiratory viruses and implementation in pandemic preparedness for novel respiratory pathogens.

Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations

Environmental perturbations are encountered by microorganisms regularly and will require metabolic adaptations to ensure an organism can survive in the newly presenting conditions. In order to study the mechanisms of metabolic adaptation in such conditions, various experimental and computational approaches have been used. Genome-scale metabolic models (GEMs) are one of the most powerful approaches to study metabolism, providing a platform to study the systems level adaptations of an organism to different environments which could otherwise be infeasible experimentally. In this review, we are describing the application of GEMs in understanding how microbes reprogram their metabolic system as a result of environmental variation. In particular, we provide the details of metabolic model reconstruction approaches, various algorithms and tools for model simulation, consequences of genetic perturbations, integration of '-omics' datasets for creating context-specific models and their application in studying metabolic adaptation due to the change in environmental conditions.

Role of circulating biomarkers in spinal muscular atrophy: insights from a new treatment era

Spinal muscular atrophy (SMA) is a lower motor neuron disease due to biallelic mutations in the SMN1 gene on chromosome 5. It is characterized by progressive muscle weakness of limbs, bulbar and respiratory muscles. The disease is usually classified in four different phenotypes (1-4) according to age at symptoms onset and maximal motor milestones achieved. Recently, three disease modifying treatments have received approval from the Food and Drug Administration (FDA) and the European Medicines Agency (EMA), while several other innovative drugs are under study. New therapies have been game changing, improving survival and life quality for SMA patients. However, they have also intensified the need for accurate biomarkers to monitor disease progression and treatment efficacy. While clinical and neurophysiological biomarkers are well established and helpful in describing disease progression, there is a great need to develop more robust and sensitive circulating biomarkers, such as proteins, nucleic acids, and other small molecules. Used alone or in combination with clinical biomarkers, they will play a critical role in enhancing patients' stratification for clinical trials and access to approved treatments, as well as in tracking response to therapy, paving the way to the development of individualized therapeutic approaches. In this comprehensive review, we describe the foremost circulating biomarkers of current significance, analyzing existing literature on non-treated and treated patients with a special focus on neurofilaments and circulating miRNA, aiming to identify and examine their role in the follow-up of patients treated with innovative treatments, including gene therapy.

Performance of targeted next-generation sequencing in the detection of respiratory pathogens and antimicrobial resistance genes for children

Introduction. Respiratory tract infection, which is associated with high morbidity and mortality, occurs frequently in children. At present, the main diagnostic method is culture. However, the low pathogen detection rate of the culture approach prevents timely and accurate diagnosis. Fortunately, next-generation sequencing (NGS) can compensate for the deficiency of culture, and its application in clinical diagnostics has become increasingly available.Gap Statement. Targeted NGS (tNGS) is a platform that can select and enrich specific regions before data enter the NGS pipeline. However, the performance of tNGS in the detection of respiratory pathogens and antimicrobial resistance genes (ARGs) in infections in children is unclear.Aim and methodology. In this study, we estimated the performance of tNGS in the detection of respiratory pathogens and ARGs in 47 bronchoalveolar lavage fluid (BALF) specimens from children using conventional culture and antimicrobial susceptibility testing (AST) as the gold standard.Results. RPIP (Respiratory Pathogen ID/AMR enrichment) sequencing generated almost 500 000 reads for each specimen. In the detection of pathogens, RPIP sequencing showed targeted superiority in detecting difficult-to-culture bacteria, including Mycoplasma pneumoniae. Compared with the results of culture, the sensitivity and specificity of RPIP were 84.4 % (confidence interval 70.5-93.5 %) and 97.7 % (95.9 -98.8%), respectively. Moreover, RPIP results showed that a single infection was detected in 10 of the 47 BALF specimens, and multiple infections were detected in 34, with the largest number of bacterial/viral coinfections. Nevertheless, there were also three specimens where no pathogen was detected. Furthermore, we analysed the drug resistance genes of specimens containing Streptococcus pneumoniae, which was detected in 25 out of 47 specimens in the study. A total of 58 ARGs associated with tetracycline, macrolide-lincosamide-streptogramin, beta-lactams, sulfonamide and aminoglycosides were identified by RPIP in 19 of 25 patients. Using the results of AST as a standard, the coincidence rates of erythromycin, tetracycline, penicillin and sulfonamides were 89.5, 79.0, 36.8 and 42.1 %, respectively.Conclusion. These results demonstrated the superiority of RPIP in pathogen detection, particularly for multiple and difficult-to-culture pathogens, as well as in predicting resistance to erythromycin and tetracycline, which has significance for the accurate diagnosis of pathogenic infection and in the guidance of clinical treatment.

Introduction and benchmarking of pyMLST: open-source software for assessing bacterial clonality using core genome MLST

Core genome multilocus sequence typing (cgMLST) has gained in popularity for bacterial typing since whole-genome sequencing (WGS) has become affordable. We introduce here pyMLST, a new complete, stand-alone, free and open source pipeline for cgMLST analysis. pyMLST can create or import a core genome database. For each gene, the first allele is aligned against the bacterial genome of interest using BLAT. Incomplete genes are aligned using MAFT. All data are stored in a SQLite database. pyMLST accepts assembly genomes or raw data (with the option pyMLST-KMA) as input. To evaluate our new tool, we selected three genome collections of major bacterial pathogens (Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus) and compared them with pyMLST, pyMLST-KMA, ChewBBACA, SeqSphere and the variant calling approach. We compared the sensitivity, precision and false-positive rate for each method with those of the variant calling approach. Minimal spanning trees were generated with each type of software to evaluate their interest in the context of a bacterial outbreak. We found that pyMLST-KMA is a convenient screening method to avoid assembling large bacterial collections. Our data showed that pyMLST (free, open source, available in Galaxy and pipeline ready) performed similarly to the commercial SeqSphere and performed better than ChewBBACA and pyMLST-KMA.

Legionella pneumophila exploits the endo-lysosomal network for phagosome biogenesis by co-opting SUMOylated Rab7

L. pneumophila strains harboring wild-type rpsL such as Lp02rpsLWT cannot replicate in mouse bone marrow-derived macrophages (BMDMs) due to induction of extensive lysosome damage and apoptosis. The mechanism of this unique infection-induced cell death remains unknown. Using a genome-wide CRISPR/Cas9 screening, we identified Hmg20a and Nol9 as host factors important for restricting strain Lp02rpsLWT in BMDMs. Depletion of Hmg20a protects macrophages from infection-induced lysosomal damage and apoptosis, allowing productive bacterial replication. The restriction imposed by Hmg20a was mediated by repressing the expression of several endo-lysosomal proteins, including the small GTPase Rab7. We found that SUMOylated Rab7 is recruited to the bacterial phagosome via SulF, a Dot/Icm effector that harbors a SUMO-interacting motif (SIM). Moreover, overexpression of Rab7 rescues intracellular growth of strain Lp02rpsLWT in BMDMs. Our results establish that L. pneumophila exploits the lysosomal network for the biogenesis of its phagosome in BMDMs.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

A Comprehensive Bioinformatics Resource Guide for Genome-Based Antimicrobial Resistance Studies

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

Heterogeneity and transmission of food safety-related enterotoxigenic Staphylococcus aureus in pig abattoirs in Hubei, China

The dissemination of Staphylococcus aureus in the pork production chain is a major food safety concern. Abattoirs can serve both as disruptor and transmitter for S. aureus. In this study, we conducted a systematic genomic epidemiology research on the prevalence, heterogeneity, and transmission of S. aureus in 3,638 samples collected from four pig abattoirs in Hubei province, China. Our findings revealed substantial heterogeneity between S. aureus recovered from samples collected at upstream (from stunning step to head-removal step) and downstream (from splitting step to chilling step) locations within the slaughter process. Overall, 966 (26.6%) samples were positive for S. aureus, with significantly higher overall prevalence for upstream samples (29.0%, 488/1,681) compared to downstream samples (24.4%, 478/1,957). Antimicrobial susceptibility testing demonstrated that the isolates from the upstream exhibited significantly higher resistance proportions to different antimicrobials than those from the downstream. Whole-genome sequencing of 126 isolates revealed that ST398 (32.9%, 23/70) and ST9 (22.9%, 16/70) were more common among upstream isolates, while ST7 (35.7%, 20/56) and ST97 (28.6%, 16/56) were most frequently observed among downstream isolates. Additionally, molecular characterization analysis demonstrated that upstream isolates possessed significantly higher enterotoxigenic potential, more antimicrobial resistance genes, and S. aureus pathogenicity islands than downstream isolates. Notably, we discovered that enterotoxigenic S. aureus could be transmitted across different slaughter stages, with knives, water, and air serving as vectors. Although slaughtering processes had a substantial effect on reducing the food safety risk posed by enterotoxigenic S. aureus, the possibility of its widespread transmission should not be disregarded. IMPORTANCE Staphylococcus aureus (S. aureus) is one of the most important foodborne pathogens, and can cause foodborne poisoning by producing enterotoxins. Pork is a preferable reservoir and its contamination often occurs during the slaughter process. Our findings revealed significant differences in the prevalence, antimicrobial resistance, and enterotoxigenic potential between the upstream and downstream isolates within the slaughter process. Also, it is imperative not to overlook enterotoxigenic S. aureus transmitted across all stages of the slaughter process, with notable vectors being knives, water, and air. These findings hold significant implications for policy-makers to reassess their surveillance projects, and underscore the importance of implementing effective control measures to minimize the risk of S. aureus contamination in pork production. Moreover, we provide a more compelling method of characterizing pathogen transmission based on core-SNPs of bacterial genomes.

Micro- and nanosystems for the detection of hemorrhagic fever viruses

Hemorrhagic fever viruses (HFVs) are virulent pathogens that can cause severe and often fatal illnesses in humans. Timely and accurate detection of HFVs is critical for effective disease management and prevention. In recent years, micro- and nano-technologies have emerged as promising approaches for the detection of HFVs. This paper provides an overview of the current state-of-the-art systems for micro- and nano-scale approaches to detect HFVs. It covers various aspects of these technologies, including the principles behind their sensing assays, as well as the different types of diagnostic strategies that have been developed. This paper also explores future possibilities of employing micro- and nano-systems for the development of HFV diagnostic tools that meet the practical demands of clinical settings.

Evaluation of whole and core genome multilocus sequence typing allele schemes for Salmonella enterica outbreak detection in a national surveillance network, PulseNet USA

Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker's gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.

Whole-genome sequencing provides insights into a novel species: Providencia hangzhouensis associated with urinary tract infections

Providencia rettgeri is a clinically significant opportunistic pathogen that is involved in urinary tract infections. Due to the resolution limitations of identification, distinguishing P. rettgeri from closely related species is challenging by commercial biochemical test systems. Here, we first reported a novel species, Providencia hangzhouensis, which had been misidentified as P. rettgeri. Exhibiting ≤91.97% average nucleotide identity (ANI) and ≤46.10% in silico DNA-DNA hybridization values with all known Providencia species, P. hangzhouensis falls well beneath the established species-defining thresholds. We conducted a population genomics analysis of P. hangzhouensis isolates worldwide. Our study revealed that P. hangzhouensis has emerged in many countries and has formed several transmission clusters. We found that P. hangzhouensis shared the highest ANI values (91.54% and 91.97%) with P. rettgeri and P. huaxiensis, respectively. The pan-genome analysis revealed that these three species possessed a similar component of pan-genomes. Two genes associated with metabolism, folE2 and ccmM, were identified to be specific to P. hangzhouensis. Furthermore, we also observed that carbapenem-resistance genes frequently occur in P. hangzhouensis with the blaIMP-27 being the most prevalent (46.15%; 36/78). The emergence of P. hangzhouensis is often accompanied by extended-spectrum β-lactamase and carbapenem-resistance genes, and calls for tailored surveillance of this species as a clinically relevant species in the future. IMPORTANCE Our study has identified and characterized a novel species, Providencia hangzhouensis, which is associated with urinary tract infections and was previously misidentified as Providencia rettgeri. Through this study, we have identified specific genes unique to P. hangzhouensis, which could serve as marker genes for rapid PCR identification. Additionally, our findings suggest that the emergence of P. hangzhouensis is often accompanied by extended-spectrum β-lactamase and carbapenem-resistance genes, emphasizing the need for attention to clinical management and the importance of accurate species identification and proper drug use.

Direct 16S/18S rRNA Gene PCR Followed by Sanger Sequencing as a Clinical Diagnostic Tool for Detection of Bacterial and Fungal Infections: a Systematic Review and Meta-Analysis

rRNA gene Sanger sequencing is being used for the identification of cultured pathogens. A new diagnostic approach is sequencing of uncultured samples by using the commercial DNA extraction and sequencing platform SepsiTest (ST). The goal was to analyze the clinical performance of ST with a focus on nongrowing pathogens and the impact on antibiotic therapy. A literature search used PubMed/Medline, Cochrane, Science Direct, and Google Scholar. Eligibility followed PRISMA-P criteria. Quality and risk of bias were assessed drawing on QUADAS-2 (quality assessment of diagnostic accuracy studies, revised) criteria. Meta-analyses were performed regarding accuracy metrics compared to standard references and the added value of ST in terms of extra found pathogens. We identified 25 studies on sepsis, infectious endocarditis, bacterial meningitis, joint infections, pyomyositis, and various diseases from routine diagnosis. Patients with suspected infections of purportedly sterile body sites originated from various hospital wards. The overall sensitivity (79%; 95% confidence interval [CI], 73 to 84%) and specificity (83%; 95% CI, 72 to 90%) were accompanied by large effect sizes. ST-related positivity was 32% (95% CI, 30 to 34%), which was significantly higher than the culture positivity (20%; 95% CI, 18 to 22%). The overall added value of ST was 14% (95% CI, 10 to 20%) for all samples. With 130 relevant taxa, ST uncovered high microbial richness. Four studies demonstrated changes of antibiotic treatment at 12% (95% CI, 9 to 15%) of all patients upon availability of ST results. ST appears to be an approach for the diagnosis of nongrowing pathogens. The potential clinical role of this agnostic molecular diagnostic tool is discussed regarding changes of antibiotic treatment in cases where culture stays negative.

Pipeline validation for the identification of antimicrobial-resistant genes in carbapenem-resistant Klebsiella pneumoniae

Antimicrobial-resistant Klebsiella pneumoniae is a global threat to healthcare and an important cause of nosocomial infections. Antimicrobial resistance causes prolonged treatment periods, high mortality rates, and economic impacts. Whole Genome Sequencing (WGS) has been used in laboratory diagnosis, but there is limited evidence about pipeline validation to parse generated data. Thus, the present study aimed to validate a bioinformatics pipeline for the identification of antimicrobial resistance genes from carbapenem-resistant K. pneumoniae WGS. Sequences were obtained from a publicly available database, trimmed, de novo assembled, mapped to the K. pneumoniae reference genome, and annotated. Contigs were submitted to different tools for bacterial (Kraken2 and SpeciesFinder) and antimicrobial resistance gene identification (ResFinder and ABRicate). We analyzed 201 K. pneumoniae genomes. In the bacterial identification by Kraken2, all samples were correctly identified, and in SpeciesFinder, 92.54% were correctly identified as K. pneumoniae, 6.96% erroneously as Pseudomonas aeruginosa, and 0.5% erroneously as Citrobacter freundii. ResFinder found a greater number of antimicrobial resistance genes than ABRicate; however, many were identified more than once in the same sample. All tools presented 100% repeatability and reproducibility and > 75% performance in other metrics. Kraken2 was more assertive in recognizing bacterial species, and SpeciesFinder may need improvements.

Contribution of Antibiotic Susceptibility Testing and CH Typing Compared to Next-Generation Sequencing for the Diagnosis of Recurrent Urinary Tract Infections Due to Genetically Identical Escherichia coli Isolates: a Prospective Cohort Study of Cystitis in Women

Recurrent cystitis is a common disease in women, mainly due to uropathogenic Escherichia coli (UPEC). For decades, typing methods now considered obsolete suggested that relapse by the same clone is dominant over reinfection, most UPEC strains being otherwise fully susceptible to antibiotics. We aimed to update these data. Thanks to a prospective study over 17 months, we recruited 323 women with cystitis. Of these, 251 of them had sporadic infection and 72 had recurrence, with 2 to 9 episodes per patient for a total of 131 UPEC isolates and 145 UPEC pairs at patient level. Phylogroups B2 (52.4%) and D (14.1%) were overall dominant, as expected due to their particular urovirulence. CH typing identified 119 distinct profiles with no CH type particularly associated with recurrence. Relapse was attested by CH typing for only 30.6% (22 out of 72), with very diverse situations ranging from all episodes due to the same clone to alternating reinfections and relapses. Next-generation sequencing confirmed the clonality for all but two of the 145 UPEC pairs. Antibiotic resistance was common for recurrent cystitis isolates (only 25 [17.2%] out of 145 UPEC pairs were fully susceptible), allowing us to predict UPEC clonality. Indeed, antibiotic susceptibility profile matched CH typing for 104 (71.7%) pairs. Finally, we demonstrated a large genetic diversity among UPEC isolates responsible for cystitis in women, even in cases of recurrence for which reinfection appeared dominant over relapse. Recurrent cystitis appears to be a heterogeneous disease requiring tailored treatment and prevention. IMPORTANCE More than half of women will experience cystitis during their lifetime. Among these women, 25% will experience a second episode within the following 6 months. It is epidemiologically important to discriminate relapses from reinfections. Relapse identification relies on long and laborious methods and might influence treatment. Therefore, the designation of time- and cost-effective strategies for this goal is of particular interest. Our work suggests using CH typing and antibiotic susceptibility profiles to type Escherichia coli, the main uropathogen.

The impact of applying various de novo assembly and correction tools on the identification of genome characterization, drug resistance, and virulence factors of clinical isolates using ONT sequencing

Oxford Nanopore sequencing technology (ONT) is currently widely used due to its affordability, simplicity, and reliability. Despite the advantage ONT has over next-generation sequencing in detecting resistance genes in mobile genetic elements, its relatively high error rate (10-15%) is still a deterrent. Several bioinformatic tools are freely available for raw data processing and obtaining complete and more accurate genome assemblies. In this study, we evaluated the impact of using mix-and-matched read assembly (Flye, Canu, Wtdbg2, and NECAT) and read correction (Medaka, NextPolish, and Racon) tools in generating complete and accurate genome assemblies, and downstream genomic analysis of nine clinical Escherichia coli isolates. Flye and Canu assemblers were the most robust in genome assembly, and Medaka and Racon correction tools significantly improved assembly parameters. Flye functioned well in pan-genome analysis, while Medaka increased the number of core genes detected. Flye, Canu, and NECAT assembler functioned well in detecting antimicrobial resistance genes (AMR), while Wtdbg2 required correction tools for better detection. Flye was the best assembler for detecting and locating both virulence and AMR genes (i.e., chromosomal vs. plasmid). This study provides insight into the performance of several read assembly and read correction tools for analyzing ONT sequencing reads for clinical isolates.

Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices

Introduction

Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States.

Methods

In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed.

Results

We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated.

Discussion

This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.

Evaluation of core genome and whole genome multilocus sequence typing schemes for Campylobacter jejuni and Campylobacter coli outbreak detection in the USA

Campylobacter is a leading causing of bacterial foodborne and zoonotic illnesses in the USA. Pulsed-field gene electrophoresis (PFGE) and 7-gene multilocus sequence typing (MLST) have been historically used to differentiate sporadic from outbreak Campylobacter isolates. Whole genome sequencing (WGS) has been shown to provide superior resolution and concordance with epidemiological data when compared with PFGE and 7-gene MLST during outbreak investigations. In this study, we evaluated epidemiological concordance for high-quality SNP (hqSNP), core genome (cg)MLST and whole genome (wg)MLST to cluster or differentiate outbreak-associated and sporadic Campylobacter jejuni and Campylobacter coli isolates. Phylogenetic hqSNP, cgMLST and wgMLST analyses were also compared using Baker's gamma index (BGI) and cophenetic correlation coefficients. Pairwise distances comparing all three analysis methods were compared using linear regression models. Our results showed that 68/73 sporadic C. jejuni and C. coli isolates were differentiated from outbreak-associated isolates using all three methods. There was a high correlation between cgMLST and wgMLST analyses of the isolates; the BGI, cophenetic correlation coefficient, linear regression model R ² and Pearson correlation coefficients were >0.90. The correlation was sometimes lower comparing hqSNP analysis to the MLST-based methods; the linear regression model R ² and Pearson correlation coefficients were between 0.60 and 0.86, and the BGI and cophenetic correlation coefficient were between 0.63 and 0.86 for some outbreak isolates. We demonstrated that C. jejuni and C. coli isolates clustered in concordance with epidemiological data using WGS-based analysis methods. Discrepancies between allele and SNP-based approaches may reflect the differences between how genomic variation (SNPs and indels) are captured between the two methods. Since cgMLST examines allele differences in genes that are common in most isolates being compared, it is well suited to surveillance: searching large genomic databases for similar isolates is easily and efficiently done using allelic profiles. On the other hand, use of an hqSNP approach is much more computer intensive and not scalable to large sets of genomes. If further resolution between potential outbreak isolates is needed, wgMLST or hqSNP analysis can be used.

Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives

Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of AMR across continents warrants systematic changes in healthcare routines and protocols. One of the fundamental issues with AMR spread is the lack of rapid diagnostic tools for pathogen identification and AMR detection. Resistance profile identification often depends on pathogen culturing and thus may last up to several days. This contributes to the misuse of antibiotics for viral infection, the use of inappropriate antibiotics, the overuse of broad-spectrum antibiotics, or delayed infection treatment. Current DNA sequencing technologies offer the potential to develop rapid infection and AMR diagnostic tools that can provide information in a few hours rather than days. However, these techniques commonly require advanced bioinformatics knowledge and, at present, are not suited for routine lab use. In this review, we give an overview of the AMR burden on healthcare, describe current pathogen identification and AMR screening methods, and provide perspectives on how DNA sequencing may be used for rapid diagnostics. Additionally, we discuss the common steps used for DNA data analysis, currently available pipelines, and tools for analysis. Direct, culture-independent sequencing has the potential to complement current culture-based methods in routine clinical settings. However, there is a need for a minimum set of standards in terms of evaluating the results generated. Additionally, we discuss the use of machine learning algorithms regarding pathogen phenotype detection (resistance/susceptibility to an antibiotic).

Effector Identification in Plant Pathogens

Effectors play a central role in determining the outcome of plant-pathogen interactions. As key virulence proteins, effectors are collectively indispensable for disease development. By understanding the virulence mechanisms of effectors, fundamental knowledge of microbial pathogenesis and disease resistance have been revealed. Effectors are also considered double-edged swords because some of them activate immunity in disease resistant plants after being recognized by specific immune receptors, which evolved to monitor pathogen presence or activity. Characterization of effector recognition by their cognate immune receptors and the downstream immune signaling pathways is instrumental in implementing resistance. Over the past decades, substantial research effort has focused on effector biology, especially concerning their interactions with virulence targets or immune receptors in plant cells. A foundation of this research is robust identification of the effector repertoire from a given pathogen, which depends heavily on bioinformatic prediction. In this review, we summarize methodologies that have been used for effector mining in various microbial pathogens which use different effector delivery mechanisms. We also discuss current limitations and provide perspectives on how recently developed analytic tools and technologies may facilitate effector identification and hence generation of a more complete vision of host-pathogen interactions. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Nuclei on the Rise: When Nuclei-Based Methods Meet Next-Generation Sequencing

In the last decade, we have witnessed an upsurge in nuclei-based studies, particularly coupled with next-generation sequencing. Such studies aim at understanding the molecular states that exist in heterogeneous cell populations by applying increasingly more affordable sequencing approaches, in addition to optimized methodologies developed to isolate and select nuclei. Although these powerful new methods promise unprecedented insights, it is important to understand and critically consider the associated challenges. Here, we provide a comprehensive overview of the rise of nuclei-based studies and elaborate on their advantages and disadvantages, with a specific focus on their utility for transcriptomic sequencing analyses. Improved designs and appropriate use of the various experimental strategies will result in acquiring biologically accurate and meaningful information.

Comparative genomic analysis provides insight into the phylogeny and potential mechanisms of adaptive evolution of Sphingobacterium sp. CZ-2

Sphingobacterium is a class of Gram-negative, non-fermentative bacilli that have received widespread attention due to their broad ecological distribution and oil degradation ability, but are rarely involved in infections. In this manuscript, a novel Sphingobacterium strain isolated from wildfire-infected tobacco leaves was named Sphingobacterium sp. CZ-2. NGS and TGS sequencing results showed a whole genome of 3.92 Mb with 40.68 mol% GC content and containing 3,462 protein-coding genes, 9 rRNA-coding genes and 50 tRNA-coding genes. Phylogenetic analysis, ANI and dDDH calculations all supported that Sphingobacterium sp. CZ-2 represented a novel species of the genus Sphingobacterium. Analysis of the specific genes of Sphingobacterium sp. CZ-2 by comparative genomics revealed that metal transport proteins encoded by the troD and cusA genes could maintain the balance of heavy metal ion concentrations in the internal environment of bacteria and avoid heavy metal toxicity while meeting the needs of growth and reproduction, and transport proteins encoded by the malG gene could keep nutrients required for the survival of bacteria. Synteny and genome evolutionary analyses of Sphingobacterium strains implicated that the gene family contraction as a major process in genome evolution, with insertional sequences leading to mutations, deletions and reversals of genes that help bacteria to withstand complex environmental changes. Complete genome sequencing and systematic comparative genomic analysis will contribute new insights into the adaptive evolution of this novel species and the genus Sphingobacterium.

Next-Generation Diagnostics for Pathogens

Next-generation sequencing (NGS) was initially developed to aid sequencing of the human genome. This molecular method is cost effective for sequencing and characterizing genomes, not only those of humans or animals but also those of bacteria and other pathogens. However, rather than sequencing a single organism, a targeted NGS method can be used to specifically amplify pathogens of interest in a clinical sample for detection and characterization by sequencing. Targeted NGS is an ideal method for ruminant syndromic testing due to its ability to detect a variety of pathogens in a sample with a single test.

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.

Utility of Direct Specimen Sequencing in Addition to Conventional Testing in Management of Infections in an Urban Referral Health Center

BACKGROUND

Direct specimen sequencing (DSS) offers the promise of enhanced pathogen detection and disease diagnosis.

METHODS

A single healthcare network, retrospective chart review over a 3-year period was completed for all cases in which DSS was submitted, in addition to conventional testing (CT) for workup of an infectious disease. We sought to compare results (concordance and discordance) from these 2 techniques in order to evaluate any additional yield from DSS over CT. Additionally, we calculated mean turnaround time (TAT) and average cost for obtaining DSS on all specimens.

RESULTS

A total of 23 patients' specimens were sent for DSS. DSS and CT concordance occurred in 91% (21/23) of cases. DSS testing was able to identify specific pathogens in 17.4% (4/23) of patients, out of which 4% (1/23) were discordant. The respective mean TAT and total cost per specimen for DSS were 6 days and $821.52 (range $573-$1590), respectively.

CONCLUSIONS

In our limited cohort of patients, there was significant concordance between the 2 testing modalities primarily due to negative tests. DSS did not provide significant additional yield in the infectious diagnosis in our cohort compared to CT. Short TAT may provide advantage in the detection of fastidious organisms, but high cost remains a limitation. Larger sample size may reveal a clinically meaningful difference.

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.

Clinical values of metagenomic next-generation sequencing in patients with severe pneumonia: a systematic review and meta-analysis

Background

Clinical values of metagenomic next-generation sequencing (mNGS) in patients with severe pneumonia remain controversial. Therefore, we conduct this meta-analysis to evaluate the diagnostic performance of mNGS for pathogen detection and its role in the prognosis of severe pneumonia.

Methods

We systematically searched the literature published in PubMed, Embase, Cochrane Library, Web of Science, Clinical Trials.gov, CNKI, Wanfang Data, and CBM from the inception to the 28th September 2022. Relevant trials comparing mNGS with conventional methods applied to patients with severe pneumonia were included. The primary outcomes of this study were the pathogen-positive rate, the 28-day mortality, and the 90-day mortality; secondary outcomes included the duration of mechanical ventilation, the length of hospital stay, and the length of stay in the ICU.

Results

Totally, 24 publications with 3220 patients met the inclusion criteria and were enrolled in this study. Compared with conventional methods (45.78%, 705/1540), mNGS (80.48%, 1233/1532) significantly increased the positive rate of pathogen detection [OR = 6.81, 95% CI (4.59, 10.11, P < 0.001]. The pooled 28-day and 90-day mortality in mNGS group were 15.08% (38/252) and 22.36% (36/161), respectively, which were significantly lower than those in conventional methods group 33.05% (117/354) [OR = 0.35, 95% CI (0.23, 0.55), P < 0.001, I² = 0%] and 43.43%(109/251) [OR = 0.34, 95% CI (0.21, 0.54), P < 0.001]. Meanwhile, adjusted treatment based on the results of mNGS shortened the length of hospital stay [MD = -2.76, 95% CI (- 3.56, - 1.96), P < 0.001] and the length of stay in ICU [MD = -4.11, 95% CI (- 5.35, - 2.87), P < 0.001].

Conclusion

The pathogen detection positive rate of mNGS was much higher than that of conventional methods. Adjusted treatment based on mNGS results can reduce the 28-day and 90-day mortality of patients with severe pneumonia, and shorten the length of hospital and ICU stay. Therefore, mNGS advised to be applied to severe pneumonia patients as early as possible in addition to conventional methods to improve the prognosis and reduce the length of hospital stay.

[Assessment of available and currently applied typing methods including genome-based methods for zoonotic pathogens with a focus on Salmonella enterica]

BACKGROUND

In recent years, whole genome sequencing (WGS) in combination with bioinformatic analyses has become state of the art in evaluating the pathogenicity/resistance potential and relatedness of bacteria. WGS analysis thus represents a central tool in the investigation of the resistance and virulence potential of pathogens, as well as their dissemination via outbreak clusters and transmission chains within the framework of molecular epidemiology. In order to gain an overview of the available genotypic and phenotypic methods used for pathogen typing of Salmonella and Shiga toxin-producing and enterohemorrhagic Escherichia coli (STEC/EHEC) in Germany at state and federal level, along with the availability of WGS-based typing and corresponding analytical methods, a survey of laboratories was conducted.

METHODS

An electronic survey of laboratories working for public health protection and consumer health protection was conducted from February to June 2020.

RESULTS AND CONCLUSION

The results of the survey showed that many of the participating laboratories provide a wide range of phenotypic and molecular methods. Molecular typing is most commonly used for species identification of Salmonella. In many cases, WGS-based methods have already been established at federal and state institutions or are in the process of being established. The Illumina sequencing technology is the most widely used technology. The survey confirms the importance of molecular biology and whole genome typing technologies for laboratories in the diagnosis of bacterial zoonotic pathogens.

Identification of highly variable sequence fragments in unmapped reads for rapid bacterial genotyping

BACKGROUND

Bacterial genotyping is a crucial process in outbreak investigation and epidemiological studies. Several typing methods such as pulsed-field gel electrophoresis, multilocus sequence typing (MLST) and whole genome sequencing are currently used in routine clinical practice. However, these methods are costly, time-consuming and have high computational demands. An alternative to these methods is mini-MLST, a quick, cost-effective and robust method based on high-resolution melting analysis. Nevertheless, no standardized approach to identify markers suitable for mini-MLST exists. Here, we present a pipeline for variable fragment detection in unmapped reads based on a modified hybrid assembly approach using data from one sequencing platform.

RESULTS

In routine assembly against the reference sequence, high variable reads are not aligned and remain unmapped. If de novo assembly of them is performed, variable genomic regions can be located in created scaffolds. Based on the variability rates calculation, it is possible to find a highly variable region with the same discriminatory power as seven housekeeping gene fragments used in MLST. In the work presented here, we show the capability of identifying one variable fragment in de novo assembled scaffolds of 21 Escherichia coli genomes and three variable regions in scaffolds of 31 Klebsiella pneumoniae genomes. For each identified fragment, the melting temperatures are calculated based on the nearest neighbor method to verify the mini-MLST's discriminatory power.

CONCLUSIONS

A pipeline for a modified hybrid assembly approach consisting of reference-based mapping and de novo assembly of unmapped reads is presented. This approach can be employed for the identification of highly variable genomic fragments in unmapped reads. The identified variable regions can then be used in efficient laboratory methods for bacterial typing such as mini-MLST with high discriminatory power, fully replacing expensive methods such as MLST. The results can and will be delivered in a shorter time, which allows immediate and fast infection monitoring in clinical practice.

Metagenomic Next-Generation Sequencing for Diagnostically Challenging Mucormycosis in Patients with Hematological Malignancies

Background

Metagenomic next-generation sequencing (mNGS) is a fast, sensitive and accurate diagnostic method for pathogens detection. However, reports on the application of mNGS in mucormycosis remain scarce.

Methods

From January 2019 to December 2021, we recruited 13 patients with hematological malignancies who were suspected of mucormycosis and completed mNGS in D20. Then we retrospectively analyze the clinical data, diagnosis, therapeutic process, and outcomes. In order to evaluate the diagnostic value of mNGS in hematological malignancies patients with suspected mucormycosis.

Results

All patients had high risk factors of Invasive Fungal Disease, including hematopoietic stem cell transplantation, immunosuppression, glucocorticoids, etc. The clinical presentations were pulmonary (n=9), rhino-orbito-cerebral (n=4). But the manifestations were nonspecific. All enrolled patients completed mNGS. And most (8/13, 61.54%) of the samples were from blood. Fungi can be detected in all specimens, including Rhizopus (n=7), Rhizomucor (n=4) and Mucor (n=2). In addition, 7/13 (53.85%) specimens were detected bacteria at the same time and virus were detected in 5/13 (38.46%). Histopathological examination was completed in 5 patients, 3 of which were completely consistent with the results of mNGS. After treatment, 6 patients were cured, while the other 7 patients died.

Conclusion

mNGS may be a complementary method for early diagnosis, especially for patients who are not suitable for histopathology examination or unable to obtain culture specimen. mNGS can also help detect bacteria and viruses simultaneously, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.