From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Omics detection and treatment of syphilis

Treponema pallidum is the source of the chronic systemic sexually transmitted illness syphilis. T. pallidum can evade immunity and spread. A hard chancre, enlarged lymph nodes, and a syphilis rash are the primary clinical signs. The condition may affect the nervous or cardiovascular system and even become fatal after being neglected. Omics technology is a cutting-edge technique that maps the entire regulatory network of gene and protein metabolism using high-throughput sequencing and other techniques, such as transcriptomics, proteomics, metabolomics, and genomics, to perform more efficient and methodical research on biological samples. Owing to the diverse and intricate biological roles and gene expression of T. pallidum, a single omics study is frequently insufficient and limited. This review focused on and summarized the use of several omics methods for investigating T. pallidum by referencing several different studies in the literature.

Optimized methods for the targeted surveillance of extended-spectrum beta-lactamase-producing Escherichia coli in human stool

Understanding transmission pathways of important opportunistic, drug-resistant pathogens, such as extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli, is essential to implementing targeted prevention strategies to interrupt transmission and reduce the number of infections. To link transmission of ESBL-producing E. coli (ESBL-EC) between two sources, single-nucleotide resolution of E. coli strains, as well as E. coli diversity within and between samples, is required. However, the microbiological methods to best track these pathogens are unclear. Here, we compared different steps in the microbiological workflow to determine the impact different pre-enrichment broths, pre-enrichment incubation times, selection in pre-enrichment, selective plating, and DNA extraction methods had on recovering ESBL-EC from human stool samples, with the aim to acquire high-quality DNA for sequencing and genomic epidemiology. We demonstrate that using a 4-h pre-enrichment in Buffered Peptone Water, plating on cefotaxime-supplemented MacConkey agar and extracting DNA using Lucigen MasterPure DNA Purification kit improves the recovery of ESBL-EC from human stool and produced high-quality DNA for whole-genome sequencing. We conclude that our optimized workflow can be applied for single-nucleotide variant analysis of an ESBL-EC from stool.IMPORTANCEDrug-resistant infections are increasingly difficult to treat with antibiotics. Preventing infections is thus highly beneficial. To do this, we need to understand how drug-resistant bacteria spread to take action to stop infection and transmission. This requires us to accurately trace these bacteria between different sources. In this study, we compared different laboratory methods to see which worked best for detecting extended-spectrum beta-lactamase (ESBL)-producing E. coli, a common cause of urinary tract or bloodstream infections, from human stool samples. We found that enriching stool in a nutrient broth for 4 h, then plating the bacterial suspension on antibiotic-selective MacConkey agar, and finally extracting DNA from the bacteria using a specific DNA purification kit resulted in improved recovery of ESBL E. coli and high-quality DNA. Sequencing multiple isolates from stool allowed us to distinguish unambiguously and at high resolution between different variants of ESBL E. coli present in stool.

Advances in DNA/RNA Sequencing and Their Applications in Acute Myeloid Leukemia (AML)

Acute myeloid leukemia (AML) is an aggressive malignancy that poses significant challenges due to high rates of relapse and resistance to treatment, particularly in older populations. While therapeutic advances have been made, survival outcomes remain suboptimal. The evolution of DNA and RNA sequencing technologies, including whole-genome sequencing (WGS), whole-exome sequencing (WES), and RNA sequencing (RNA-Seq), has significantly enhanced our understanding of AML at the molecular level. These technologies have led to the discovery of driver mutations and transcriptomic alterations critical for improving diagnosis, prognosis, and personalized therapy development. Furthermore, single-cell RNA sequencing (scRNA-Seq) has uncovered rare subpopulations of leukemia stem cells (LSCs) contributing to disease progression and relapse. However, widespread clinical integration of these tools remains limited by costs, data complexity, and ethical challenges. This review explores recent advancements in DNA/RNA sequencing in AML and highlights both the potential and limitations of these techniques in clinical practice.

The presence of genes encoding carbapenem-hydrolyzing oxacillinase and lack of carbapenem resistance in non-baumannii Acinetobacter misidentified as Acinetobacter baumannii causing bloodstream infections in a tertiary hospital over a 3-year period

OBJECTIVE

This study aims to analyze the genomic and clinical characteristics of Non-baumannii Acinetobacter strains misidentified as A. baumannii, causing bloodstream infections (BSIs) in our hospital.

MATERIALS AND METHODS

Whole genome sequencing was performed and average nucleotide identity (ANI) was analyzed. Susceptibility testing was conducted using micro-broth methods. The distribution of antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) was examined using online software tools. The prevalence of virulence factors (VFs) was investigated through nucleotide coding sequence comparisons. Genetic structures of blaOXA genes were analyzed by Gcluster software. Clinical information was collected from electronic medical records for patient characterization.

RESULTS

ANI analysis identified five strains as Acinetobacter pittii, with the remaining four identified as A. geminorum, A. nosocomialis, A. soli and A. bereziniae. The GC content of all isolates was less than 38.9 % except for A. soli 16,294. All Non-baumannii Acinetobacter strains were relatively susceptible to antibiotics, except for one A. pittii isolate. Nine blaOXA variants were identified in seven isolates, with two isolates co-carrying 2 different types of blaOXA. Twenty-four insertion sequences (ISs) were identified, with ISAba and IS17 being the primary ISs. Five A. pittii isolates shared the same genetic structures around blaOXA. Genes related to adherence, immune modulation, and nutritional/metabolic factors were the most frequent. Few VFs were detected in A. soli 16,294 and A.bereziniae 14,325.

CONCLUSIONS

The presence of carbapenem hydrolyzing oxacillinase encoding genes did not confer carbapenem resistance, possibly due to the lack of ISs in the blaOXA flanking sequences. Different blaOXA variants within distinct strains shared the same genetic structures, suggesting potential for multidrug resistance development, which warrants our attention.

The correlation between intestinal colonization and infection of carbapenem-resistant Klebsiella pneumoniae: A systematic review

As a widely spread Gram-negative bacteria, Klebsiella pneumoniae (KP) mainly causes acquired infections in hospitals, such as lung infections, urinary tract infections, and bloodstream infections. In recent years, the number of multidrug-resistant KP strains has increased dramatically, posing a great threat to human health. Carbapenem-resistant KP (CRKP) can be colonized in human body, especially in gastrointestinal tract, and some colonized patients can be infected during hospitalization, among which invasive operation, underlying disease, admission to intensive care unit, antibiotic use, severity of the primary disease, advanced age, operation, coma, and renal failure are common risk factors for secondary infection. Active screening and preventive measures can effectively prevent the occurrence of CRKP infection. Based on the epidemiological status, this study aims to discuss the correlation between colonization and secondary infection induced by CRKP and risk factors for their happening and provide some reference for nosocomial infection prevention and control.

Genomic Insights into the Pathogenicity and Drug-Resistance of a Bacillus cereus Isolated from Human Teeth

Background

Bacillus cereus is a common bacterium found in the environment. Some strains can cause food poisoning, and very few can cause clinically severe infections, leading to death. Here, we characterized the genome sequence of B. cereus LIN78 isolated from teeth with deep caries and compared it with those of 25 other related species.

Methods

Third-generation sequencing technology, bacteriological analyses, biochemistry, and mass spectrometry were applied to characterize the drug-resistance genes and virulence factors of B. cereus LIN78.

Results

The complete genome sequence of B. cereus Lin78 consists of 5647 genes distributed on a circular chromosome, a 393 kbp plasmid, and 928 pseudogenes (37.4% of whole-genome DNA). The LIN78 genome contains 14 sets of 16s, 23s, and 5s ribosomal RNA operons; 106 tRNA genes, one tmRNA, 12 genomic islands, six prophases, 64 repeats; 37 antibiotic-resistant genes; and 1119 putative virulence genes, including enterotoxins and cytolysins. The B. cereus LIN78 genome carries multiple copies of non-ribosomal polypeptide synthetase (NRPS) and post-translationally modified peptides (RiPPs). Phylogenetic analysis of the 26 B. cereus strains showed that B. cereus LIN78 is evolutionarily closely related to B. thuringiensis ATCC 10792 and B. cereus ATCC 14579.

Conclusion

The newly isolated B. cereus carries many virulence genes, including enterotoxins and hemolysins, similar to B. anthracis, and multiple antibiotic resistance genes. These findings suggest that the strain has a potential risk of causing disease. Our studies are vital for further exploration of the evolution of B. cereus, its pathogenic mechanisms, and the control and treatment of bacterial infections.

Integrative genomics would strengthen AMR understanding through ONE health approach

Emergence of drug-induced antimicrobial resistance (AMR) forms a crippling health and economic crisis worldwide, causing high mortality from otherwise treatable diseases and infections. Next Generation Sequencing (NGS) has significantly augmented detection of culture independent microbes, potential AMR in pathogens and elucidation of mechanisms underlying it. Here, we review recent findings of AMR evolution in pathogens aided by integrated genomic investigation strategies inclusive of bacteria, virus, fungi and AMR alleles. While AMR monitoring is dominated by data from hospital-related infections, we review genomic surveillance of both biotic and abiotic components involved in global AMR emergence and persistence. Identification of pathogen-intrinsic as well as environmental and/or host factors through robust genomics/bioinformatics, along with monitoring of type and frequency of antibiotic usage will greatly facilitate prediction of regional and global patterns of AMR evolution. Genomics-enabled AMR prediction and surveillance will be crucial - in shaping health and economic policies within the One Health framework to combat this global concern.

Understanding the potential role of whole genome sequencing (WGS) in managing patients with gonorrhoea: A systematic review of WGS use on human pathogens in individual patient care

OBJECTIVES

The utility of whole genome sequencing (WGS) to inform sexually transmitted infection (STI) patient management is unclear. Timely WGS data might support clinical management of STIs by characterising epidemiological links and antimicrobial resistance profiles. We conducted a systematic review of clinical application of WGS to any human pathogen that may be transposable to gonorrhoea.

METHODS

We searched six databases for articles published between 01/01/2010-06/02/2023 that reported on real/near real-time human pathogen WGS to inform clinical intervention. All article types from all settings were included. Findings were analysed using narrative synthesis.

RESULTS

We identified 12,179 articles, of which eight reported applications to inform tuberculosis (n = 7) and gonorrhoea (n = 1) clinical patient management. WGS data were successfully used as an adjunct to clinical and epidemiological data to enhance contact-tracing (n = 2), inform antimicrobial therapy (n = 5) and identify cross-contamination (n = 1). WGS identified gonorrhoea transmission chains that were not established via partner notification. Future applications could include insights into pathogen exposure detected within sexual networks for targeted patient management.

CONCLUSIONS

While there was some evidence of WGS use to provide individualised tuberculosis and gonorrhoea treatment, the eight identified studies contained few participants. Future research should focus on testing WGS intervention effectiveness and examining ethical considerations of STI WGS use.

Characterization of an outbreak caused by Elizabethkingia miricola using Fourier-transform infrared (FTIR) spectroscopy

Fourier-transform infrared (FTIR) spectroscopy has the potential to be used for bacterial typing and outbreak characterization. We evaluated FTIR for the characterization of an outbreak caused by Elizabethkingia miricola. During the 2020-2021 period, 26 isolates (23 clinical and 3 environmental) were collected and analyzed by FTIR (IR Biotyper) and core-genome MLST (cgMLST), in addition to antimicrobial susceptibility testing. FTIR spectroscopy and cgMLST showed that 22 of the isolates were related to the outbreak, including the environmental samples, with only one discordance between both methods. Then, FTIR is useful for E. miricola typing and can be easily implemented in the laboratory.

Whole Genome Sequencing Highlights the Pathogenic Profile in Nocardia Keratitis

Purpose

Nocardia keratitis is a serious and sight-threatening condition. This study aims to reveal the virulence and antimicrobial resistance gene profile of Nocardia strains using whole genome sequencing.

Methods

Whole-genome sequencing was performed on 23 cornea-derived Nocardia strains. Together with genomic data from the respiratory tract and the environment, 141 genomes were then utilized for phylogenetic and pan-genome analyses, followed by virulence and antibiotic resistance analysis. The correlations between virulence genes and pathogenicity were experimentally validated, including the characteristics of Nocardia colonies and clinical and histopathological evaluations of Nocardia keratitis mice models.

Results

Whole-genome sequencing of 141 Nocardia strains revealed a mean of 220 virulence genes contributed to bacterial pathogenesis. The mce gene family analysis led to the categorization of strains from the cornea into groups A, B, and C. The colonies of group C had the largest diameter, height, and fastest growth rate. The size of corneal ulcers and the clinical scores showed a significant increase in mouse models induced by group C. The relative expression levels of pro-inflammatory cytokines (CD4, IFN-γ, IL-6Rα, and TNF-α) in the lesion area exhibited an increasing trend from group A to group C. Antibiotic resistance genes (ARGs) spanned nine distinct drug classes, four resistance mechanisms, and seven primary antimicrobial resistance gene families.

Conclusions

Whole genome sequencing highlights the pathogenic role of mce gene family in Nocardia keratitis. Its distribution pattern may contribute to the distinct characteristics of the growth of Nocardia colonies and the clinical severity of the mice models.

High-throughput omics technologies in inflammatory bowel disease

Inflammatory bowel disease (IBD) is a chronic, relapsing intestinal disease. Elucidation of the pathogenic mechanisms of IBD requires high-throughput technologies (HTTs) to effectively obtain and analyze large amounts of data. Recently, HTTs have been widely used in IBD, including genomics, transcriptomics, proteomics, microbiomics, metabolomics and single-cell sequencing. When combined with endoscopy, the application of these technologies can provide an in-depth understanding on the alterations of intestinal microbe diversity and abundance, the abnormalities of signaling pathway-mediated immune responses and functionality, and the evaluation of therapeutic effects, improving the accuracy of early diagnosis and treatment of IBD. This review comprehensively summarizes the development and advancement of HTTs, and also highlights the challenges and future directions of these technologies in IBD research. Although HTTs have made striking breakthrough in IBD, more standardized methods and large-scale dataset processing are still needed to achieve the goal of personalized medicine.

The clinical and epidemiological impacts of whole genomic sequencing on bacterial and virological agents

Whole Genome Sequencing (WGS) is a molecular biology tool consisting in the sequencing of the entire genome of a given organism. Due to its ability to provide the finest available resolution of bacterial and virological genetics, it is used at several levels in the field of infectiology. On an individual scale and through application of a single technique, it enables the typological identification and characterization of strains, the characterization of plasmids, and enhanced search for resistance genes and virulence factors. On a collective scale, it enables the characterization of strains and the determination of phylogenetic links between different microorganisms during community outbreaks and healthcare-associated epidemics. The information provided by WGS enables real-time monitoring of strain-level epidemiology on a worldwide scale, and facilitates surveillance of the resistance dissemination and the introduction or emergence of pathogenic variants in humans or their environment. There are several possible approaches to completion of an entire genome. The choice of one method rather than another is essentially dictated by the matrix, either a clinical sample or a culture isolate, and the clinical objective. WGS is an advanced technology that remains costly despite a gradual decrease in its expenses, potentially hindering its implementation in certain laboratories and thus its use in routine microbiology. Even though WGS is making steady inroads as a reference method, efforts remain needed in view of so harmonizing its interpretations and decreasing the time to generation of conclusive results.

A comprehensive technology strategy for microbial identification and contamination investigation in the sterile drug manufacturing facility-a case study

Objective

A comprehensive strategy for microbial identification and contamination investigation during sterile drug manufacturing was innovatively established in this study, mainly based on MALDI-TOF MS for the identification and complemented by sequencing technology on strain typing.

Methods

It was implemented to monitor the bacterial contamination of a sterile drug manufacturing facility, including its bacterial distribution features and patterns. In three months, two hundred ninety-two samples were collected covering multiple critical components of raw materials, personnel, environment, and production water.

Results

Based on our strategy, the bacterial profile across the production process was determined: 241/292 bacterial identities were obtained, and Staphylococcus spp. (40.25%), Micrococcus spp.(11.20%), Bacillus spp. (8.30%), Actinobacteria (5.81%), and Paenibacillus spp. (4.56%) are shown to be the most dominant microbial contaminants. With 75.8% species-level and 95.4% genus-level identification capability, MALDI-TOF MS was promising to be a first-line tool for environmental monitoring routine. Furthermore, to determine the source of the most frequently occurring Staphylococcus cohnii, which evidenced a widespread presence in the entire process, a more discriminating S. cohnii whole-genome SNP typing method was developed to track the transmission routes. Phylogenetic analysis based on SNP results indicated critical environment contamination is highly relevant to personnel flow in this case. The strain typing results provide robust and accurate information for the following risk assessment step and support effective preventive and corrective measures.

Conclusion

In general, the strategy presented in this research will facilitate the development of improved production and environmental control processes for the pharmaceutical industry, and give insights about how to provide more sound and reliable evidence for the optimization of its control program.

Cancer epigenetics: from laboratory studies and clinical trials to precision medicine

Epigenetic dysregulation is a common feature of a myriad of human diseases, particularly cancer. Defining the epigenetic defects associated with malignant tumors has become a focus of cancer research resulting in the gradual elucidation of cancer cell epigenetic regulation. In fact, most stages of tumor progression, including tumorigenesis, promotion, progression, and recurrence are accompanied by epigenetic alterations, some of which can be reversed by epigenetic drugs. The main objective of epigenetic therapy in the era of personalized precision medicine is to detect cancer biomarkers to improve risk assessment, diagnosis, and targeted treatment interventions. Rapid technological advancements streamlining the characterization of molecular epigenetic changes associated with cancers have propelled epigenetic drug research and development. This review summarizes the main mechanisms of epigenetic dysregulation and discusses past and present examples of epigenetic inhibitors in cancer diagnosis and treatment, with an emphasis on the development of epigenetic enzyme inhibitors or drugs. In the final part, the prospect of precise diagnosis and treatment is considered based on a better understanding of epigenetic abnormalities in cancer.

Genomic characterization of Bacillus cereus isolated from food poisoning cases revealed the mechanism of toxin production

Introduction

Bacillus cereus is a ubiquitous opportunistic human pathogen that causes food intoxications worldwide. However, the genomic characteristics and pathogenic mechanisms of B. cereus are still unclear.

Methods

Here, we isolated and purified nine strains of B. cereus (LY01-LY09) that caused vomiting, diarrhea and other symptoms from four foodborne outbreaks happened in Guizhou Province in southwest China from June to September 2021. After colony observation, Gram staining, microscopic examination and biochemical test, they were identified as B. cereus. The genomic characteristics, phylogenetic relationships and virulence factors of the isolated strains were analyzed at the genome level. Genome sequencing, comparative genomic analysis, secondary metabolite analysis and quantitative PCR were utilized to give a thorough exploration of the strains.

Results

We obtained the genome maps of LY01-LY09 and found that LY01-LY09 had a complex interspecific relationship with B. anthracis and B. thuringiensis. We also observed a contraction of gene families in LY01-LY09, and the contracted families were mainly associated with prophage, which contributed to the species diversity of B. cereus. The Hsp20 gene family underwent a rapid evolution in LY01-LY09, which facilitated the adaptation of the strains to adverse environmental conditions. Moreover, the LY01-LY09 strains exhibited a higher copy number in the non-ribosomal polypeptide synthetase (NRPS) genes and carried the complete cereulide synthetase (ces) gene cluster sequences. Considering that the NRPS system is a classical regulatory mechanism for emetic toxin synthesis, we hypothesized that LY01-LY09 could synthesize emetic toxins through the regulation of ces gene clusters by the NRPS system.

Discussion

These findings are important for further investigation into the evolutionary relationship between B. cereus and their related species, as well as the underlying mechanisms governing the synthesis and secretion of bacterial toxins.

Streptomyces albireticuli lung infection managed as a pulmonary air cyst: a case report and literature review

Streptomyces, the largest genus in the Streptomycetaceae family and a prolific producer of antibacterial drugs, is a saprophytic soil organism that rarely causes invasive infections. Here we report a case of necrotic pneumonia caused by Streptomyces albireticuli in a 75-year-old man who presented with progressive chest tightness and dyspnea. Streptomyces albireticuli was isolated from his bronchoalveolar lavage fluid and identified through whole-genome sequencing (WGS) and phylogenetic analysis. The patient responded satisfactorily to clarithromycin therapy. The findings of this study may enhance our vigilance in identifying visceral infections caused by Streptomyces.

Genetics of congenital heart disease

During embryonic development, the cardiovascular system and the central nervous system exhibit a coordinated developmental process through intricate interactions. Congenital heart disease (CHD) refers to structural or functional abnormalities that occur during embryonic or prenatal heart development and is the most common congenital disorder. One of the most common complications in CHD patients is neurodevelopmental disorders (NDD). However, the specific mechanisms, connections, and precise ways in which CHD co-occurs with NDD remain unclear. According to relevant research, both genetic and non-genetic factors are significant contributors to the co-occurrence of sporadic CHD and NDD. Genetic variations, such as chromosomal abnormalities and gene mutations, play a role in the susceptibility to both CHD and NDD. Further research should aim to identify common molecular mechanisms that underlie the co-occurrence of CHD and NDD, possibly originating from shared genetic mutations or shared gene regulation. Therefore, this review article summarizes the current advances in the genetics of CHD co-occurring with NDD, elucidating the application of relevant gene detection techniques. This is done with the aim of exploring the genetic regulatory mechanisms of CHD co-occurring with NDD at the gene level and promoting research and treatment of developmental disorders related to the cardiovascular and central nervous systems.

Next-Generation Sequencing to Study the DNA Interaction

Next-generation sequencing (NGS) has transformed genomics by allowing researchers to sequence DNA and RNA at highest speed, accuracy, and cost-effectiveness. Researchers investigate DNA interactions with the help next-generation sequencing with a great deal of information. Over the last decade, NGS technologies have advanced significantly, with the development of several platforms, including Illumina, PacBio, and Oxford Nanopore, each offering distinct advantages and uses. The use of next-generation sequencing (NGS) has aided in the discovery of genetic variations, gene expression patterns, and epigenetic modifications connected with a variety of diseases, including cancer, neurological disorders, and infectious diseases. By identifying these regions, we can control the expression of genes, cellular signaling pathways, and other key biological processes. NGS is an effective method for researching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting in new discoveries and applications in medicine, environmental sciences, and other fields.

Determination of Ideal Factors for Early Adoption and Standardization of Metagenomic Next-generation Sequencing for Respiratory System Infections

BACKGROUND

Metagenomic next-generation sequencing (mNGS) demonstrates great promise as a diagnostic tool for determining the cause of pathogenic infections. The standard diagnostic procedures (SDP) include smears and cultures and are typically viewed as less sensitive and more time-consuming when compared to mNGS. There are concerns about the logistics and ease of transition from SDP to mNGS. mNGS lacks standardization of collection processes, databases, and sequencing. Additionally, there is the burden of training clinicians on interpreting mNGS results.

OBJECTIVE

Until now, few studies have explored factors that could be used as early adoption candidates to ease the transition between SDP and mNGS. This study evaluated 123 patients who had received both SDP and mNGS and compared several variables across a diagnostic test evaluation.

METHODS

The diagnostic test evaluation observed metrics such as sensitivity, specificity, positive and negative likelihood ratios (PLR, NLR), positive and negative predictive values (PPV, NPV), and accuracy. Factors included various sample sources such as bronchoalveolar lavage fluid (BALF), lung tissue, and cerebral spinal fluid (CSF). An additional factor observed was the patient's immune status.

RESULTS

Pathogen detection was found to be significantly greater for mNGS for total patients, BALF sample source, CSF sample source, and non-immunocompromised patients (p<0.05). Pathogen detection was found to be insignificant for lung tissue sample sources and immunocompromised patients. Sensitivity, PLR, NLR, PPV, NPV, and accuracy appeared to be higher with mNGS for the total patients, BALF sample source, and non-immunocompromised patients when compared with SDP (p<0.05).

CONCLUSION

With higher metrics in sensitivity, specificity, PLR, NLR, PPV, NPV, and accuracy for overall patients, mNGS may prove a better diagnostic tool than SDP. When addressing sample sources, mNGS for BALF-collected samples appeared to have higher scores than SDP for the same metrics. When patients were in a non-immunocompromised state, mNGS also demonstrated greater diagnostic benefits to BALF and overall patients compared to SDP. This study demonstrates that using BALF as a sample source and selecting non-immunocompromised patients may prove beneficial as early adoption factors for mNGS standard protocol. Such a study may pave the road for mNGS as a routine clinical method for determining the exact pathogenic etiology of lung infections.

Treatment and diagnosis of severe KPC-producing Klebsiella pneumoniae infections: a perspective on what has changed over last decades

Antimicrobial resistance is a global health threat. Among Gram-negative bacteria, resistance to carbapenems, a class of β-lactam antibiotics, is usually a proxy for difficult-to-treat resistance, since carbapenem-resistant organisms are often resistant to many classes of antibiotics. Carbapenem resistance in the Gram-negative pathogen Klebsiella pneumoniae is mostly due to the production of carbapenemases, enzymes able to hydrolyze carbapenems, and K. pneumoniae carbapenemase (KPC)-type enzymes are overall the most prevalent carbapenemases in K. pneumoniae. In the last decade, the management of severe infections due to KPC-producing K. pneumoniae (KPC-Kp) in humans has presented many peculiar challenges to clinicians worldwide. In this perspective, we discuss how the treatment of severe KPC-Kp infections has evolved over the last decades, guided by the accumulating evidence from clinical studies, and how recent advances in diagnostics have allowed to anticipate identification of KPC-Kp in infected patients.KEY MESSAGESIn the last decade, the management of severe infections due to KPC-Kp has presented many peculiar challenges to clinicians worldwideFollowing the introduction in clinical practice of novel β-lactam/β-lactamase inhibitor combinations and novel β-lactams active against KPC-producing bacteria, the management of severe KPC-Kp infections has witnessed a remarkable evolutionTreatment of severe KPC-Kp infections is a highly dynamic process, in which the wise use of novel antimicrobials should be accompanied by a continuous refinement based on evolving clinical evidence and laboratory diagnostics.

Whole-genome sequencing of carbapenem-resistant Enterobacterales isolates in southeast Louisiana reveals persistent genetic clusters spanning multiple locations

BACKGROUND

We investigated 51 g-negative carbapenem-resistant Enterobacterales (CRE) isolates collected from 22 patients over a five-year period from six health care institutions in the Ochsner Health network in southeast Louisiana.

METHODS

Short genomic reads were generated using Illumina sequencing and assembled for each isolate. Isolates were classified as Enterobacter spp. (n = 20), Klebsiella spp. (n = 30), and Escherichia coli (n = 1) and grouped into 19 different multi-locus sequence types (MLST). Species and patient-specific core genomes were constructed representing ∼50% of the chromosomal genome.

RESULTS

We identified two sets of patients with genetically related infections; in both cases, the related isolates were collected > 6 months apart, and in one case, the isolates were collected in different locations. On the other hand, we identified four sets of patients with isolates of the same species collected within 21 days from the same location; however, none had genetically related infections. Genes associated with resistance to carbapenem drugs (blaKPC and/or blaCTX-M-15) were found in 76% of the isolates. We found three blaKPC variants (blaKPC-2, blaKPC-3, and blaKPC-4) associated with four different Enterobacter MLST variants, and two blaKPC variants (blaKPC-2, blaKPC-3) associated with seven different Klebsiella MLST variants.

CONCLUSIONS

Molecular surveillance is increasingly becoming a powerful tool to understand bacterial spread in both community and clinical settings. This study provides evidence that genetically related infections in clinical settings do not necessarily reflect temporal associations, and vice versa. Our results also highlight the regional genomic and resistance diversity within related bacterial lineages.

Phenotypic drug-susceptibility profiles and genetic analysis based on whole-genome sequencing of Mycobacterium avium complex isolates in Thailand

Mycobacterium avium complex (MAC) infections are a significant clinical challenge. Determining drug-susceptibility profiles and the genetic basis of drug resistance is crucial for guiding effective treatment strategies. This study aimed to determine the drug-susceptibility profiles of MAC clinical isolates and to investigate the genetic basis conferring drug resistance using whole-genome sequencing (WGS) analysis. Drug-susceptibility profiles based on minimum inhibitory concentration (MIC) assays were determined for 38 MAC clinical isolates (12 Mycobacterium avium and 26 Mycobacterium intracellulare). Mutations associated with drug resistance were identified through genome analysis of these isolates, and their phylogenetic relationships were also examined. Drug resistance, based on MIC values, was most commonly observed for moxifloxacin (81.6%), followed by linezolid (78.9%), clarithromycin (44.7%) and amikacin (36.8%). We identified specific mutations associated with resistance to amikacin. These include the rrs mutation at C464T in amikacin intermediate-resistance M. avium, and two mutations at T250A and G1453T in amikacin non-susceptible M. intracellulare. Mutations in rrl at A2058G, A2059C and A2059G were potentially linked to clarithromycin resistance. MAC clinical isolates not susceptible to linezolid exhibited mutations in rplC at G237C and C459T, as well as two rplD mutations at G443A and A489G. GyrB substitution Thr521Ala (T521A) was identified in moxifloxacin non-susceptible isolates, which may contribute to this resistance. A phylogeny of our MAC isolates revealed high levels of genetic diversity. Our findings suggest that the standard treatment regimen for MAC infections using moxifloxacin, linezolid, clarithromycin and amikacin may be driving development of resistance, potentially due to specific mutations. The combination of phenotypic and genotypic susceptibility testing can be valuable in guiding the clinical use of drugs for the treatment of MAC infections.

Complete Genome Sequence and Probiotic Properties of Pediococcus acidilactici CLP03 Isolated from Healthy Felis catus

Probiotics are available from various sources, including the gastrointestinal tract of healthy animals. In this study, Pediococcus acidilactici was isolated for the first time from Felis catus and evaluated for its functionality. The findings revealed that P. acidilactici CLP03 exhibited inhibitory properties against pathogenic bacteria (E. coli, Salmonella, S. aureus, P. aeruginosa, and L. monocytogenes). Then, survival of strains exposed to pH 2.5, 0.3% bile salts, 0.5% bile salts, and gastrointestinal fluids was 63.97%, 98.84%, 87.95%, and 52.45%, respectively. Also, P. acidilactici CLP03 demonstrated high hydrophobicity (69.63-82.03%) and self-aggregation (73.51-81.44%), negative for hemolytic, and was susceptible to clindamycin. Finally, the scavenging rates of DPPH, ABTS, and O2- were 53.55%, 54.81%, and 85.13%, respectively, which demonstrated that the strain CLP03 has good oxidation resistance. All these characteristics contribute to the survival, colonization, and functionality of the strain in the gastrointestinal tract, indicating their excellent probiotic potential. On the other hand, animal experiments (KM mice, randomly assigned to four groups) showed that the gavage of CLP03 had no toxic effects on mice, increased the serum SOD content, and decreased the MDA and BUN contents, which revealed gavage of CLP03 significantly increased the antioxidant capacity of mice in vivo. In addition, complete genome annotation showed that P. acidilactici CLP03 had 1976 CDS genes, and the numbers of CRISPR, gene islands, and phages were 8, 3, and 6, respectively. In conclusion, P. acidilactici CLP03 could be a candidate functional cat probiotic to enhance animal health and welfare.

A qualitative process evaluation using the behaviour change wheel approach: Did a whole genome sequence report form (SRF) used to reduce nosocomial SARS-CoV-2 within UK hospitals operate as anticipated?

PURPOSE

The aim of this study was to conduct a process evaluation of a whole-genome sequence report form (SRF) used to reduce nosocomial SARS-CoV-2 through changing infection prevention and control (IPC) behaviours within the COVID-19 pandemic.

METHODS

We used a three-staged design. Firstly, we described and theorized the purported content of the SRF using the behaviour change wheel (BCW). Secondly, we used inductive thematic analysis of one-to-one interviews (n = 39) to explore contextual accounts of using the SRF. Thirdly, further deductive analysis gauged support for the intervention working as earlier anticipated.

RESULTS

It was possible to theorize the SRF using the BCW approach and visualize it within a simple logic model. Inductive thematic analyses identified the SRF's acceptability, ease of use and perceived effectiveness. However, major challenges to embedding it in routine practice during the unfolding COVID-19 crisis were reported. Notwithstanding this insight, deductive analysis showed support for the putative intervention functions 'Education', 'Persuasion' and 'Enablement'; behaviour change techniques '1.2 Problem solving', '2.6 Biofeedback', '2.7 Feedback on outcomes of behaviour' and '7.1 Prompts and cues'; and theoretical domains framework domains 'Knowledge' and 'Behavioural regulation'.

CONCLUSIONS

Our process evaluation of the SRF, using the BCW approach to describe and theorize its content, provided granular support for the SRF working to change IPC behaviours as anticipated. However, our complementary inductive thematic analysis highlighted the importance of the local context in constraining its routine use. For SRFs to reach their full potential in reducing nosocomial infections, further implementation research is needed.

Revolutionizing Medical Microbiology: How Molecular and Genomic Approaches Are Changing Diagnostic Techniques

Molecular and genomic approaches have revolutionized medical microbiology by offering faster and more accurate diagnostic techniques for infectious diseases. Traditional methods, which include culturing microbes and biochemical testing, are time-consuming and may not detect antibiotic-resistant strains. In contrast, molecular and genomic methods, including polymerase chain reaction (PCR)-based techniques and whole-genome sequencing, provide rapid and precise detection of pathogens, early-stage diseases, and antibiotic-resistant strains. These approaches have advantages such as high sensitivity and specificity, the potential for targeted therapies, and personalized medicine. However, implementing molecular and genomic techniques faces challenges related to cost, equipment, expertise, and data analysis. Ethical and legal considerations regarding patient privacy and genetic data usage also arise. Nonetheless, the future of medical microbiology lies in the widespread adoption of molecular and genomic approaches, which can lead to improved patient outcomes and the identification of antibiotic-resistant strains. Continued advancements, education, and exploration of ethical implications are necessary to fully harness the potential of molecular and genomic techniques in medical microbiology.

P-DOR, an easy-to-use pipeline to reconstruct bacterial outbreaks using genomics

SUMMARY

Bacterial Healthcare-Associated Infections (HAIs) are a major threat worldwide, which can be counteracted by establishing effective infection control measures, guided by constant surveillance and timely epidemiological investigations. Genomics is crucial in modern epidemiology but lacks standard methods and user-friendly software, accessible to users without a strong bioinformatics proficiency. To overcome these issues we developed P-DOR, a novel tool for rapid bacterial outbreak characterization. P-DOR accepts genome assemblies as input, it automatically selects a background of publicly available genomes using k-mer distances and adds it to the analysis dataset before inferring a Single-Nucleotide Polymorphism (SNP)-based phylogeny. Epidemiological clusters are identified considering the phylogenetic tree topology and SNP distances. By analyzing the SNP-distance distribution, the user can gauge the correct threshold. Patient metadata can be inputted as well, to provide a spatio-temporal representation of the outbreak. The entire pipeline is fast and scalable and can be also run on low-end computers.

AVAILABILITY AND IMPLEMENTATION

P-DOR is implemented in Python3 and R and can be installed using conda environments. It is available from GitHub https://github.com/SteMIDIfactory/P-DOR under the GPL-3.0 license.

Mycobacterium tuberculosis complex whole-genome sequencing in New York State: Implementation of a reduced phenotypic drug susceptibility testing algorithm

Whole-genome sequencing (WGS) can predict drug resistance and antimicrobial susceptibility in Mycobacterium tuberculosis complex (MTBC) and has shown promise in partially replacing culture-based phenotypic drug susceptibility testing (pDST). We performed a two-year side by side study comparing the prediction of drug resistance and antimicrobial susceptibility by WGS molecular DST (mDST) to pDST to determine resistance at the critical concentration by Mycobacterial Growth Indicator Tube (MGIT) and agar proportion testing. Negative predictive values of WGS results were consistently high for the first-line drugs: rifampin (99.9%), isoniazid (99.0%), pyrazinamide (98.5%), and ethambutol (99.8%); the rates of resistance to these drugs, among strains in our population, are 2.9%, 10.4%, 46.3%, and 2.3%, respectively. WGS results were available an average 8 days earlier than first-line MGIT pDST. Based on these findings, we implemented a new testing algorithm with an updated WGS workflow in which strains predicted pan-susceptible were no longer tested by pDST. This algorithm was applied to 1177 isolates between October 2018 and September 2020, eliminating pDST for 66.6% of samples and reducing pDST for an additional 22.0%. This algorithm change resulted in faster turnaround times and decreased cost while maintaining comprehensive antimicrobial susceptibility profiles of all culture-positive MTBC cases in New York.

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.

Emerging Genomic Trends on Rabies Virus in Davao Region, Philippines, 2018-2021

Rabies, caused by the rabies virus (RABV), remains a significant public health issue in the Philippines despite efforts to control it. To eliminate rabies by 2030, effective surveillance strategies are crucial. In this study, we examined RABV evolution and phylodynamics in the Davao Region using genome sequences from Davao City and nearby provinces. We adapted the RABV ARTIC Protocol for Oxford Nanopore High-Throughput Sequencing to optimize workflow efficiency under limited resources. Comparing new virus samples collected from June 2019 to June 2021 (n = 38) with baseline samples from June 2018 to May 2019 (n = 49), new sub-clades were observed in the phylogenetic tree, suggesting divergence from older variants that were previously undetected. Most of the new viruses belonged to the Asian SEA4_A1.1.1 lineage, but new (SEA4_B1 and SEA4_B1.1) and emerging (SEA4_B1.1_E1) lineages that have never been reported in the Philippines were also identified. The baseline study reported phylogeographic clustering of RABV isolates from the same areas. However, this pattern was disrupted in the current biosurveillance, with variants detected in areas outside the original cluster. Furthermore, our findings revealed significant transmission routes between Davao City and neighboring provinces, contrasting with the predominantly intra-city transmission observed in the baseline study. These results underscore the need for ongoing and timely genomic surveillance to monitor genetic diversity changes and the emergence of novel strains, as well as to track alterations in transmission pathways. Implementing cost-effective next-generation sequencing workflows will facilitate the integration of genomic surveillance into rabies control programs, particularly in resource-limited settings. Collaborations between different sectors can empower local laboratories and experts in genomic technologies and analysis.

QUIRMIA-A Phenotype-Based Algorithm for the Inference of Quinolone Resistance Mechanisms in Escherichia coli

OBJECTIVES

Quinolone resistance in Escherichia coli occurs mainly as a result of mutations in the quinolone-resistance-determining regions of gyrA and parC, which encode the drugs' primary targets. Mutational alterations affecting drug permeability or efflux as well as plasmid-based resistance mechanisms can also contribute to resistance, albeit to a lesser extent. Simplifying and generalizing complex evolutionary trajectories, low-level resistance towards fluoroquinolones arises from a single mutation in gyrA, while clinical high-level resistance is associated with two mutations in gyrA plus one mutation in parC. Both low- and high-level resistance can be detected phenotypically using nalidixic acid and fluoroquinolones such as ciprofloxacin, respectively. The aim of this study was to develop a decision tree based on disc diffusion data and to define epidemiological cut-offs to infer resistance mechanisms and to predict clinical resistance in E. coli. This diagnostic algorithm should provide a coherent genotype/phenotype classification, which separates the wildtype from any non-wildtype and further differentiates within the non-wildtype.

METHODS

Phenotypic susceptibility of 553 clinical E. coli isolates towards nalidixic acid, ciprofloxacin, norfloxacin and levofloxacin was determined by disc diffusion, and the genomes were sequenced. Based on epidemiological cut-offs, we developed a QUInolone Resistance Mechanisms Inference Algorithm (QUIRMIA) to infer the underlying resistance mechanisms responsible for the corresponding phenotypes, resulting in the categorization as "susceptible" (wildtype), "low-level resistance" (non-wildtype) and "high-level resistance" (non-wildtype). The congruence of phenotypes and whole genome sequencing (WGS)-derived genotypes was then assigned using QUIRMIA- and EUCAST-based AST interpretation.

RESULTS

QUIRMIA-based inference of resistance mechanisms and sequencing data were highly congruent (542/553, 98%). In contrast, EUCAST-based classification with its binary classification into "susceptible" and "resistant" isolates failed to recognize and properly categorize low-level resistant isolates.

CONCLUSIONS

QUIRMIA provides a coherent genotype/phenotype categorization and may be integrated in the EUCAST expert rule set, thereby enabling reliable detection of low-level resistant isolates, which may help to better predict outcome and to prevent the emergence of clinical resistance.

A Genomic Snapshot of Antibiotic-ResistantEnterococcus faecalis within Public Hospital Environments in South Africa

Enterococci are among the most common opportunistic hospital pathogens. This study used whole-genome sequencing (WGS) and bioinformatics to determine the antibiotic resistome, mobile genetic elements, clone and phylogenetic relationship of Enterococcus faecalis isolated from hospital environments in South Africa. This study was carried out from September to November 2017. Isolates were recovered from 11 frequently touched sites by patients and healthcare workers in different wards at 4 levels of healthcare (A, B, C, and D) in Durban, South Africa. Out of the 245 identified E. faecalis isolates, 38 isolates underwent whole-genome sequencing (WGS) on the Illumina MiSeq platform, following microbial identification and antibiotic susceptibility tests. The tet(M) (31/38, 82%) and erm(C) (16/38, 42%) genes were the most common antibiotic-resistant genes found in isolates originating from different hospital environments which corroborated with their antibiotic resistance phenotypes. The isolates harboured mobile genetic elements consisting of plasmids (n = 11) and prophages (n = 14) that were mostly clone-specific. Of note, a large number of insertion sequence (IS) families were found on the IS3 (55%), IS5 (42%), IS1595 (40%), and Tn3 transposons the most predominant. Microbial typing using WGS data revealed 15 clones with 6 major sequence types (ST) belonging to ST16 (n = 7), ST40 (n = 6), ST21 (n = 5), ST126 (n = 3), ST23 (n = 3), and ST386 (n = 3). Phylogenomic analysis showed that the major clones were mostly conserved within specific hospital environments. However, further metadata insights revealed the complex intraclonal spread of these E. faecalis major clones between the sampling sites within each specific hospital setting. The results of these genomic analyses will offer insights into antibiotic-resistantE. faecalis in hospital environments relevant to the design of optimal infection prevention strategies in hospital settings.

Hybridization chain reaction-assisted enzyme cascade genosensor for the detection of Listeria monocytogenes

Foodborne diseases caused by pathogens may threaten public health and the social economy. We demonstrated a method for identifying pathogenic Listeria monocytogenes using DNA logic operations. To achieve accurate species distinguishing, three specific sequences of Listeria monocytogenes genomic DNA were screened out and used as the feature sequences. Three complementary probes with tag modification were designed as sensing elements and exert affinity for magnetic beads, glucose oxidase (GOx), and horseradish peroxidase (HRP). To obtain a digital output (YES/NO answer) for rapid determination, a Boolean logic function was employed. Three sensing probes enabled the recognition of the target sequence (input) and the formation of a target DNA/probe hybrid. Through magnetic separation and affinity binding events, the target DNA/probes hybrid led to the construction of GOx/HRP enzyme cascade, which produced a visualized color signal (output) in the presence of substrates, glucose, and 3, 3', 5, 5'-tetramethylbenzidine (TMB). A hybridization chain reaction (HCR) was coupled with this sensing scaffold to increase the binding of the enzyme cascade and amplify the output signal. The logical functional biosensor showed high selectivity of Listeria monocytogenes over other Listeria species. This sensing platform provides a simple, sensitive, and highly specific method for detecting Listeria monocytogenes.

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.

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.

Genomic characterization and assessment of pathogenic potential of Legionella spp. isolates from environmental monitoring

Several species in the genus Legionella are known to cause an acute pneumonia when the aerosols containing the bacteria from man-made water systems are inhaled. The disease is usually caused by Legionella pneumophila, but other species have been implicated in the infection. The disease is frequently manifested as an outbreak, which means several people are affected when exposed to the common source of Legionella contamination. Therefor environmental surveillance which includes isolation and identification of Legionella is performed routinely. However, usually no molecular or genome-based methods are employed in further characterization of the isolates during routine environmental monitoring. During several years of such monitoring, isolates from different geographical locations were collected and 39 of them were sequenced by hybrid de novo approach utilizing short and long sequencing reads. In addition, the isolates were typed by standard culture and MALDI-TOF method. The sequencing reads were assembled and annotated to produce high-quality genomes. By employing discriminatory genome typing, four potential new species in the Legionella genus were identified, which are yet to be biochemically and morphologically characterized. Moreover, functional annotations concerning virulence and antimicrobial resistance were performed on the sequenced genomes. The study contributes to the knowledge on little-known non-pneumophila species present in man-made water systems and establishes support for future genetic relatedness studies as well as understanding of their pathogenic potential.

Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings

The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment - including animals, plants, soil, and water - are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance.

Prime Editing in Mammals: The Next Generation of Precision Genome Editing

The recently established prime editor (PE) system is regarded as next-generation gene-editing technology. This methodology can install any base-to-base change as well as insertions and deletions without the requirement for double-stranded break formation or donor DNA templates; thus, it offers more targeting flexibility and greater editing precision than conventional CRISPR-Cas systems or base editors. In this study, we introduce the basic principles of PE and then review its most recent progress in terms of editing versatility, specificity, and efficiency in mammals. Next, we summarize key considerations regarding the selection of PE variants, prime editing guide RNA (pegRNA) design rules, and the efficiency and accuracy evaluation of PE. Finally, we highlight and discuss how PE can assist in a wide range of biological studies and how it can be applied to make precise genomic corrections in animal models, which paves the way for curing human diseases.

Recent advances in metagenomic analysis of different ecological niches for enhanced biodegradation of recalcitrant lignocellulosic biomass

Lignocellulose wastes stemming from agricultural residues can offer an excellent opportunity as alternative energy solutions in addition to fossil fuels. Besides, the unrestrained burning of agricultural residues can lead to the destruction of the soil microflora and associated soil sterilization. However, the difficulties associated with the biodegradation of lignocellulose biomasses remain as a formidable challenge for their sustainable management. In this respect, metagenomics can be used as an effective option to resolve such dilemma because of its potential as the next generation sequencing technology and bioinformatics tools to harness novel microbial consortia from diverse environments (e.g., soil, alpine forests, and hypersaline/acidic/hot sulfur springs). In light of the challenges associated with the bulk-scale biodegradation of lignocellulose-rich agricultural residues, this review is organized to help delineate the fundamental aspects of metagenomics towards the assessment of the microbial consortia and novel molecules (such as biocatalysts) which are otherwise unidentifiable by conventional laboratory culturing techniques. The discussion is extended further to highlight the recent advancements (e.g., from 2011 to 2022) in metagenomic approaches for the isolation and purification of lignocellulolytic microbes from different ecosystems along with the technical challenges and prospects associated with their wide implementation and scale-up. This review should thus be one of the first comprehensive reports on the metagenomics-based analysis of different environmental samples for the isolation and purification of lignocellulose degrading enzymes.

An Improved Diagnostic of the Mycobacterium tuberculosis Drug Resistance Status by Applying a Decision Tree to Probabilities Assigned by the CatBoost Multiclassifier of Matrix Metalloproteinases Biomarkers

In this work, we discuss an opportunity to use a set of the matrix metalloproteinases MMP-1, MMP-8, and MMP-9 and the tissue inhibitor TIMP, the concentrations of which can be easily obtained via a blood test from patients suffering from tuberculosis, as the biomarker for a fast diagnosis of the drug resistance status of Mycobacterium tuberculosis. The diagnostic approach is based on machine learning with the CatBoost system, which has been supplied with additional postprocessing. The latter refers not only to the simple probabilities of ML-predicted outcomes but also to the decision tree-like procedure, which takes into account the presence of strict zeros in the primary set of probabilities. It is demonstrated that this procedure significantly elevates the accuracy of distinguishing between sensitive, multi-, and extremely drug-resistant strains.

The effect of sequencing and assembly on the inference of horizontal gene transfer on chromosomal and plasmid phylogenies

The spread of antibiotic resistance genes on plasmids is a threat to human and animal health. Phylogenies of bacteria and their plasmids contain clues regarding the frequency of plasmid transfer events, as well as the co-evolution of plasmids and their hosts. However, whole genome sequencing data from diverse ecological or clinical bacterial samples are rarely used to study plasmid phylogenies and resistance gene transfer. This is partially due to the difficulty of extracting plasmids from short-read sequencing data. Here, we use both short- and long-read sequencing data of 24 clinical extended-spectrum [Formula: see text]-lactamase (ESBL)-producing Escherichia coli to estimate chromosomal and plasmid phylogenies. We compare the impact of different sequencing and assembly methodologies on these phylogenies and on the inference of horizontal gene transfer. We find that chromosomal phylogenies can be estimated robustly with all methods, whereas plasmid phylogenies have more variable topology and branch lengths across the methods used. Specifically, hybrid methods that use long reads to resolve short-read assemblies (HybridSPAdes and Unicycler) perform better than those that started from long reads during assembly graph generation (Canu). By contrast, the inference of plasmid and antibiotic resistance gene transfer using a parsimony-based criterion is mostly robust to the choice of sequencing and assembly method. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Advantages and challenges of metagenomic sequencing for the diagnosis of pulmonary infectious diseases

Objective

We aim to familiarize the application status of metagenomic sequencing in diagnosing pulmonary infections, to compare metagenomic sequencing with traditional diagnostic methods, to conclude the advantages and limitations of metagenomic sequencing, and to provide some advice for clinical practice and some inspiration for associated researches.

Data Sources

The data were obtained from peer‐reviewed literature, white papers, and meeting reports.

Results

This review focused on the applications of untargeted metagenomic sequencing in lungs infected by bacteria, viruses, fungi, chlamydia pneumoniae, Mycoplasma pneumoniae, parasites, and other pathogens. Compared with conventional diagnostic methods, metagenomic sequencing is better in detecting novel, rare, and unexpected pathogens and being applied in co‐infections. Meanwhile, it can also provide more comprehensive information about pathogens. However, metagenomic sequencing still has limitations. Also, the situations that should be applied in and how the results should be interpreted are discussed in this review.

Conclusion

Metagenomic sequencing improves efficiency to identify pathogens compared with traditional diagnostic methods and can be applied in clinical diagnosis. However, the technology of metagenomic sequencing still needs to be improved. Also, clinicians should learn more about when to use metagenomic sequencing and how to interpret its results.

Laboratory Misidentifications Resulting from Taxonomic Changes to Bacillus cereus Group Species, 2018-2022

Whole-genome sequencing (WGS) is being applied increasingly to Bacillus cereus group species; however, misinterpretation of WGS results may have severe consequences. We report 3 cases, 1 of which was an outbreak, in which misinterpretation of B. cereus group WGS results hindered communication within public health and industrial laboratories.

Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases

Next-generation sequencing (NGS) technologies have become increasingly available for use in the clinical microbiology diagnostic environment. There are three main applications of these technologies in the clinical microbiology laboratory: whole genome sequencing (WGS), targeted metagenomics sequencing and shotgun metagenomics sequencing. These applications are being utilized for initial identification of pathogenic organisms, the detection of antimicrobial resistance mechanisms and for epidemiologic tracking of organisms within and outside hospital systems. In this review, we analyze these three applications and provide a comprehensive summary of how these applications are currently being used in public health, basic research, and clinical microbiology laboratory environments. In the public health arena, WGS is being used to identify and epidemiologically track food borne outbreaks and disease surveillance. In clinical hospital systems, WGS is used to identify multi-drug-resistant nosocomial infections and track the transmission of these organisms. In addition, we examine how metagenomics sequencing approaches (targeted and shotgun) are being used to circumvent the traditional and biased microbiology culture methods to identify potential pathogens directly from specimens. We also expand on the important factors to consider when implementing these technologies, and what is possible for these technologies in infectious disease diagnosis in the next 5 years.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

Rapid Oxford Nanopore Technologies MinION Sequencing Workflow for Campylobacter jejuni Identification in Broilers on Site—A Proof-of-Concept Study

Campylobacter is recognised as one of the most important foodborne bacteria, with a worldwide health and socioeconomic impact. This bacterium is one of the most important zoonotic players in poultry, where efficient and fast detection methods are required. Current official culture methods for Campylobacter enumeration in poultry usually include >44 h of culture and >72 h for identification, thus requiring at least five working shifts (ISO/TS 10272-2:2017). Here, we have assembled a portable sequencing kit composed of the Bento Lab and the MinION and developed a workflow for on-site farm use that is able to detect and report the presence of Campylobacter from caecal samples in less than five hours from sampling time, as well as the relationship of Campylobacter with other caecal microbes. Beyond that, our workflow may offer a cost-effective and practical method of microbiologically monitoring poultry at the farm. These results would demonstrate the possibility of carrying out rapid on-site screening to monitor the health status of the poultry farm/flock during the production chain.

Bacterial and fungal communities in tracheal aspirates of intubated COVID-19 patients: a pilot study

Co-infections with bacterial or fungal pathogens could be associated with severity and outcome of disease in COVID-19 patients. We, therefore, used a 16S and ITS-based sequencing approach to assess the biomass and composition of the bacterial and fungal communities in endotracheal aspirates of intubated COVID-19 patients. Our method combines information on bacterial and fungal biomass with community profiling, anticipating the likelihood of a co-infection is higher with (1) a high bacterial and/or fungal biomass combined with (2) predominance of potentially pathogenic microorganisms. We tested our methods on 42 samples from 30 patients. We observed a clear association between microbial outgrowth (high biomass) and predominance of individual microbial species. Outgrowth of pathogens was in line with the selective pressure of antibiotics received by the patient. We conclude that our approach may help to monitor the presence and predominance of pathogens and therefore the likelihood of co-infections in ventilated patients, which ultimately, may help to guide treatment.