Whole-Genome Sequencing for Investigating a Health Care-Associated Outbreak of Carbapenem-Resistant Acinetobacter baumannii

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.

Gram-Negative ESKAPE Bacteria Surveillance in COVID-19 Pandemic Exposes High-Risk Sequence Types of Acinetobacter baumannii MDR in a Tertiary Care Hospital

The interruption of bacteriological surveillance due to the COVID-19 pandemic brought serious consequences, such as the collapse of health systems and the possible increase in antimicrobial resistance. Therefore, it is necessary to know the rate of resistance and its associated mechanisms in bacteria causing hospital infections during the pandemic. The aim of this work was to show the phenotypic and molecular characteristics of antimicrobial resistance in ESKAPE bacteria in a Mexican tertiary care hospital in the second and third years of the pandemic. For this purpose, during 2021 and 2022, two hundred unduplicated strains of the ESKAPE group (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii) were collected from various clinical sources and categorized by resistance according to the CLSI. An analysis of variance (ANOVA) complemented by the Tukey test was performed to search for changes in antimicrobial susceptibility profiles during the study period. Finally, the mechanisms of resistance involved in carbapenem resistance were analyzed, and the search for efflux pumps and high-risk sequence types in A. baumannii was performed by multilocus analysis (MLST). The results showed no changes in K. pneumoniae resistance during the period analyzed. Decreases in quinolone resistance were identified in E. coli (p = 0.039) and P. aeruginosa (p = 0.03). Interestingly, A. baumannii showed increases in resistance to penicillins (p = 0.004), aminoglycosides (p < 0.001, p = 0.027), carbapenems (p = 0.027), and folate inhibitors (p = 0.001). Several genes involved in carbapenem resistance were identified (blaNDM, blaVIM, blaOXA, blaKPC, blaOXA-40, and blaOXA-48) with a predominance of blaOXA-40 and the adeABCRS efflux pump in A. baumannii. Finally, MLST analysis revealed the presence of globally distributed sequence types (ST369 and ST758) related to hospital outbreaks in other parts of the world. The results presented demonstrate that the ESKAPE group has played an important role during the COVID-19 pandemic as nosocomial antibiotic-resistant pathogens and in particular A. baumannii MDR as a potential reservoir of resistance genes. The implications of the increases in antimicrobial resistance in pathogens of the ESKAPE group and mainly in A. baumannii during the COVID-19 pandemic are analyzed and discussed.

Whole-Genome Analysis of Bordetella pertussis MT27 Isolates from School-Associated Outbreaks: Single-Nucleotide Polymorphism Diversity and Threshold of the Outbreak Strains

Bordetella pertussis, the causative agent of whooping cough, can cause pertussis outbreaks in humans, especially in school-aged children. Here, we performed whole-genome sequencing of 51 B. pertussis isolates (epidemic strain MT27) collected from patients infected during 6 school-associated outbreaks lasting less than 4 months. We compared their genetic diversity with that of 28 sporadic isolates (non-outbreak MT27 isolates) based on single-nucleotide polymorphisms (SNPs). Our temporal SNP diversity analysis revealed a mean SNP accumulation rate (time-weighted average) of 0.21 SNPs/genome/year during the outbreaks. The outbreak isolates showed a mean of 0.74 SNP differences (median, 0; range, 0 to 5) between 238 isolate pairs, whereas the sporadic isolates had a mean of 16.12 SNP differences (median, 17; range 0 to 36) between 378 isolate pairs. A low SNP diversity was observed in the outbreak isolates. Receiver operating characteristic analysis demonstrated that the optimal cutoff value to distinguish between the outbreak and sporadic isolates was 3 SNPs (Youden's index of 0.90 with a true-positive rate of 0.97 and a false-positive rate of 0.07). Based on these results, we propose an epidemiological threshold of ≤3 SNPs per genome as a reliable marker of B. pertussis strain identity during pertussis outbreaks that span less than 4 months. IMPORTANCE Bordetella pertussis is a highly infectious bacterium that easily causes pertussis outbreaks in humans, especially in school-aged children. In detection and investigation of outbreaks, excluding non-outbreak isolates is important for understanding the bacterial transmission routes. Currently, whole-genome sequencing is widely used for outbreak investigations, and the genetic relatedness of outbreak isolates is assessed based on differences in the number of single-nucleotide polymorphisms (SNPs) in the genomes of different isolates. The optimal SNP threshold defining strain identity has been proposed for many bacterial pathogens, but not for B. pertussis. In this study, we performed whole-genome sequencing of 51 B. pertussis outbreak isolates and identified a genetic threshold of ≤3 SNPs per genome as a marker defining the strain identity during pertussis outbreaks. This study provides a useful marker for identifying and analyzing pertussis outbreaks and can serve as a basis for future epidemiological studies on pertussis.

Colistin Resistance in Acinetobacter baumannii: Molecular Mechanisms and Epidemiology

Acinetobacter baumannii is recognized as a clinically significant pathogen causing a wide spectrum of nosocomial infections. Colistin was considered a last-resort antibiotic for the treatment of infections caused by multidrug-resistant A. baumannii. Since the reintroduction of colistin, a number of mechanisms of colistin resistance in A. baumannii have been reported, including complete loss of LPS by inactivation of the biosynthetic pathway, modifications of target LPS driven by the addition of phosphoethanolamine (PEtN) moieties to lipid A mediated by the chromosomal pmrCAB operon and eptA gene-encoded enzymes or plasmid-encoded mcr genes and efflux of colistin from the cell. In addition to resistance to colistin, widespread heteroresistance is another feature of A. baumannii that leads to colistin treatment failure. This review aims to present a critical assessment of relevant published (>50 experimental papers) up-to-date knowledge on the molecular mechanisms of colistin resistance in A. baumannii with a detailed review of implicated mutations and the global distribution of colistin-resistant strains.

Molecular tracking of carbapenem-resistant Acinetobacter baumannii clinical isolates: a multicentre study over a 4-year period across eastern China

Introduction. Colonization by carbapenem-resistant Acinetobacter baumannii (CRAB) causes therapeutic and economic problems for critically ill patients.Gap Statement. The analysis of CRAB in China was limited to certain regions.Aims. To investigate the antibiotic susceptibility, molecular characterization and clonal relationship among CRAB isolates from multiple hospitals of eastern China.Methodology. Isolates from 29 tertiary hospitals from September 2015 to September 2018 were recovered. All strains were analysed using antimicrobial susceptibility testing to detect their tolerance. PCR was also used to detect multiple β-lactamase genes. After multilocus sequence typing (MLST) of seven house-keeping genes. eBURST was used to assess clonal complexes and explore evolutionary relationships.Results. All isolates showed resistance to carbapenems, while remaining susceptible to colistin and tigecycline. All isolates were detected with bla _OXA-51 gene by PCR, and 80.1 % harboured the bla _OXA-23 gene. The prevalence of bla_OXA-23 gene was remarkably increased from 50.7 % in 2015 to 90.5 % in 2018. Other genes such as bla _OXA-24, bla _OXA-58, bla _IMP-2/4, bla _VIM-2, bla _SHV, bla _AmpC and bla _TEM were also obtained. While bla _KPC, bla _NDM-1, bla _IMP-4 and bla _SIM-1 were not found in these strains. MLST showed all isolates could be divided into 26 known sequence types (STs) and ten novel STs and 47.2 % isolates belong to ST195 and ST208. eBURST revealed clonal complex 92 as the major clonal complex (98.4 %), which includes 88.5 % (23/26) of known STs and 80 % (8/10) of unknown STs. Phylogenetic analysis also found that almost all CRAB isolates could cluster into one lineage, suggesting an epidemic of this CRAB lineage. This indicated severe nosocomial infections of CRAB in multiple hospitals of eastern China.Conclusion. An outbreak of ST195 and ST208 CRAB-resistant clones with bla _OXA-23 gene might be happening in multiple hospitals in eastern China.

A novel repeat sequence-based PCR (rep-PCR) using specific repeat sequences of Mycobacterium intracellulare as a DNA fingerprinting

Repetitive sequence-based PCR (rep-PCR) is a potential epidemiological technique that can provide high-throughput genotype fingerprints of heterogeneous Mycobacterium strains rapidly. Previously published rep-PCR primers, which are based on nucleotide sequences of Gram-negative bacteria may have low specificity for mycobacteria. Moreover, it was difficult to ensure the continuity of the study after the commercial rep-PCR kit was discontinued. Here, we designed a novel rep-PCR for Mycobacterium intracellulare, a major cause of nontuberculous mycobacterial pulmonary disease with frequent recurrence. We screened the 7,645 repeat sequences for 200 fragments from the genome of M. intracellulare ATCC 13950 in silico, finally generating five primers with more than 90% identity for a total of 226 loci in the genome. The five primers could make different band patterns depending on the genome of three different M. intracellulare strains using an in silico test. The novel rep-PCR with the five primers was conducted using 34 bacterial samples of 7 species containing 25 M. intracellulare clinical isolates, compared with previous published rep-PCRs. This shows distinguished patterns depending on species and blotting assay for 6 species implied the sequence specificity of the five primers. The Designed rep-PCR had a 95-98% of similarity value in the reproducibility test and showed 7 groups of fingerprints in M. intracellulare strains. Designed rep-PCR had a correlation value of 0.814 with VNTR, reference epidemiological method. This study provides a promising genotype fingerprinting method for tracing the recurrence of heterogeneous M. intracellulare.

Systems Biology: New Insight into Antibiotic Resistance

Over the past few decades, antimicrobial resistance (AMR) has emerged as an important threat to public health, resulting from the global propagation of multidrug-resistant strains of various bacterial species. Knowledge of the intrinsic factors leading to this resistance is necessary to overcome these new strains. This has contributed to the increased use of omics technologies and their extrapolation to the system level. Understanding the mechanisms involved in antimicrobial resistance acquired by microorganisms at the system level is essential to obtain answers and explore options to combat this resistance. Therefore, the use of robust whole-genome sequencing approaches and other omics techniques such as transcriptomics, proteomics, and metabolomics provide fundamental insights into the physiology of antimicrobial resistance. To improve the efficiency of data obtained through omics approaches, and thus gain a predictive understanding of bacterial responses to antibiotics, the integration of mathematical models with genome-scale metabolic models (GEMs) is essential. In this context, here we outline recent efforts that have demonstrated that the use of omics technology and systems biology, as quantitative and robust hypothesis-generating frameworks, can improve the understanding of antibiotic resistance, and it is hoped that this emerging field can provide support for these new efforts.

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.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Epidemiological and Genetic Characteristics of Clinical Carbapenem-Resistant Acinetobacter baumannii Strains Collected Countrywide from Hospital Intensive Care Units (ICUs) in China

Acinetobacter baumannii is one of the key Gram-negative pathogens that can cause serious nosocomial infections. In China, a large proportion of clinical A. baumannii strains are multidrug resistant, among which strains resistant to carbapenems are particularly worrisome, as infections caused by such strains may limit the choice of existing antibiotics. We conducted a nationwide and genome-based surveillance on the prevalence and antibiotic susceptibility profile of carbapenem-resistant A. baumannii (CRAB) strains collected from intensive care units (ICUs) in hospitals in different provinces and investigated the routes of transmission and mechanism of resistance by whole-genome sequencing and phylogenetic analysis. We found that CRAB strains were prevalent in 71.4% (55/77) of the ICUs surveyed. Clonal spread of CRAB was found in 37.6% (29/77) of ICUs and a total of 22 different clones were identified. Most clones were transmissible within one ICU, but up to six clones could be detected in at least three hospitals. In addition, carbapenem-hydrolysing class D β-lactamases (CHDL) were found to be mainly responsible for carbapenem-resistance in A. baumannii and the ST2 global-clone is the predominant type of CRAB in China. Importantly, we found that CRAB isolates currently exhibited extremely low rate of resistance to colistin (0.4%) and tigecycline (2.5%), but a high rate of resistance to ceftazidime-avibactam (70.2%). Findings in this work shall facilitate development of appropriate antimicrobial regimens for treatment of CRAB infections. Further surveillance and research on the evolutionary and epidemiological features of clinical CRAB strains are necessary.

Whole-Genome Sequencing Elucidates the Epidemiology of Multidrug-Resistant Acinetobacter baumannii in an Intensive Care Unit

The nosocomial pathogen Acinetobacter baumannii is a frequent cause of healthcare-acquired infections, particularly in critically ill patients, and is of serious concern due to its potential for acquired multidrug resistance. Whole-genome sequencing (WGS) is increasingly used to obtain a high-resolution view of relationships between isolates, which helps in controlling healthcare-acquired infections. Here, we conducted a retrospective study to identify epidemic situations and assess the percentage of transmission in intensive care units (ICUs). Multidrug-resistant A. baumannii (MDR-AB) were continuously isolated from the lower respiratory tract of different patients (at the first isolation in our ICU). We performed WGS, pulsed-field gel electrophoresis (PFGE), and multilocus-sequence typing (MLST) analyses to elucidate bacterial relatedness and to compare the performance of conventional methods with WGS for typing MDR-AB. From June 2017 to August 2018, A. baumannii complex strains were detected in 124 of 796 patients during their ICU stays, 103 of which were MDR-AB. Then we subjected 70 available MDR-AB strains to typing with WGS, PFGE, and MLST. Among the 70 A. baumannii isolates, 38 (54.29%) were isolated at admission, and 32(45.71%) were acquisition isolates. MLST identified 12 unique sequence types, a novel ST (ST2367) was founded. PFGE revealed 16 different pulsotypes. Finally, 38 genotypes and 23 transmissions were identified by WGS. Transmission was the main mode of MDR-AB acquisition in our ICU. Our results demonstrated that WGS was a discriminatory technique for epidemiological healthcare-infection studies. The technique should greatly benefit the identification of epidemic situations and controlling transmission events in the near future.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.