Whole-Genome Sequencing of Bacterial Pathogens: the Future of Nosocomial Outbreak Analysis

Association of Virulence, Biofilm, and Antimicrobial Resistance Genes with Specific Clonal Complex Types of Listeria monocytogenes

Precise classification of foodborne pathogen Listeria monocytogenes is a necessity in efficient foodborne disease surveillance, outbreak detection, and source tracking throughout the food chain. In this study, a total of 150 L. monocytogenes isolates from various food products, food processing environments, and clinical sources were investigated for variations in virulence, biofilm formation, and the presence of antimicrobial resistance genes based on their Whole-Genome Sequences. Clonal complex (CC) determination based on Multi-Locus Sequence Typing (MLST) revealed twenty-eight CC-types including eight isolates representing novel CC-types. The eight isolates comprising the novel CC-types share the majority of the known (cold and acid) stress tolerance genes and are all genetic lineage II, serogroup 1/2a-3a. Pan-genome-wide association analysis by Scoary using Fisher's exact test identified eleven genes specifically associated with clinical isolates. Screening for the presence of antimicrobial and virulence genes using the ABRicate tool uncovered variations in the presence of Listeria Pathogenicity Islands (LIPIs) and other known virulence genes. Specifically, the distributions of actA, ecbA, inlF, inlJ, lapB, LIPI-3, and vip genes across isolates were found to be significantly CC-dependent while the presence of ami, inlF, inlJ, and LIPI-3 was associated with clinical isolates specifically. In addition, Roary-derived phylogenetic grouping based on Antimicrobial-Resistant Genes (AMRs) revealed that the thiol transferase (FosX) gene was present in all lineage I isolates, and the presence of the lincomycin resistance ABC-F-type ribosomal protection protein (lmo0919_fam) was also genetic-lineage-dependent. More importantly, the genes found to be specific to CC-type were consistent when a validation analysis was performed with fully assembled, high-quality complete L. monocytogenes genome sequences (n = 247) extracted from the National Centre for Biotechnology Information (NCBI) microbial genomes database. This work highlights the usefulness of MLST-based CC typing using the Whole-Genome Sequence as a tool in classifying isolates.

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.

Using source-associated mobile genetic elements to identify zoonotic extraintestinal E. coli infections

A one-health perspective may provide new and actionable information about Escherichia coli transmission. E. coli colonizes a broad range of vertebrates, including humans and food-production animals, and is a leading cause of bladder, kidney, and bloodstream infections in humans. Substantial evidence supports foodborne transmission of pathogenic E. coli strains from food animals to humans. However, the relative contribution of foodborne zoonotic E. coli (FZEC) to the human extraintestinal disease burden and the distinguishing characteristics of such strains remain undefined. Using a comparative genomic analysis of a large collection of contemporaneous, geographically-matched clinical and meat-source E. coli isolates (n = 3111), we identified 17 source-associated mobile genetic elements - predominantly plasmids and bacteriophages - and integrated them into a novel Bayesian latent class model to predict the origins of clinical E. coli isolates. We estimated that approximately 8 % of human extraintestinal E. coli infections (mostly urinary tract infections) in our study population were caused by FZEC. FZEC strains were equally likely to cause symptomatic disease as non-FZEC strains. Two FZEC lineages, ST131-H22 and ST58, appeared to have particularly high virulence potential. Our findings imply that FZEC strains collectively cause more urinary tract infections than does any single non-E. coli uropathogenic species (e.g., Klebsiella pneumoniae). Our novel approach can be applied in other settings to identify the highest-risk FZEC strains, determine their sources, and inform new one-health strategies to decrease the heavy public health burden imposed by extraintestinal E. coli infections.

Population genomics and pathotypic evaluation of the bacterial leaf blight pathogen of rice reveals rapid evolutionary dynamics of a plant pathogen

The Xanthomonas oryzae pv. oryzae (Xoo) is a bacterial pathogen causing bacterial blight disease in rice, resulting in significant yield reductions of up to 50% in rice production. Despite its serious threat to food production globally, knowledge of its population structure and virulence evolution is relatively limited. In this study, we employed whole-genome sequencing to explore the diversity and evolution of Xoo in the main rice-growing areas of China over the past 30 years. Using phylogenomic analysis, we revealed six lineages. CX-1 and CX-2 primarily contained Xoo isolates from South China, while CX-3 represented Xoo isolates from North China. Xoo isolates belonging to CX-5 and CX-6 were the most prevalent across all studied areas, persisting as dominant lineages for several decades. Recent sporadic disease outbreaks were primarily caused by Xoo isolates derived from the two major lineages, CX-5 and CX-6, although Xoo isolates from other lineages also contributed to these outbreaks. The lineage and sub-lineage distributions of Xoo isolates were strongly correlated with their geographical origin, which was found to be mainly determined by the planting of the two major rice subspecies, indica and japonica. Moreover, large-scale virulence testing was conducted to evaluate the diversity of pathogenicity for Xoo. We found rapid virulence evolution against rice, and its determinant factors included the genetic background of Xoo, rice resistance genes, and planting environment of rice. This study provides an excellent model for understanding the evolution and dynamics of plant pathogens in the context of their interactions with their hosts, which are shaped by a combination of geographical conditions and farming practices. The findings of this study may have important implications for the development of effective strategies for disease management and crop protection in rice production systems.

16S-23S rRNA Internal Transcribed Spacer Region (ITS) Sequencing: A Potential Molecular Diagnostic Tool for Differentiating Lactococcus garvieae and Lactococcus petauri

Lactococcus garvieae is the etiological agent of lactococcosis, a clinically and economically significant infectious disease affecting farmed rainbow trout. L. garvieae had been considered the only cause of lactococcosis for a long time; however, L. petauri, another species of the genus Lactococcus, has lately been linked to the same disease. The genomes and biochemical profiles of L. petauri and L. garvieae have a high degree of similarity. Traditional diagnostic tests currently available cannot distinguish between these two species. The aim of this study was to use the transcribed spacer (ITS) region between 16S rRNA and 23S rRNA as a potential useful molecular target to differentiate L. garvieae from L. petauri, saving time and money compared to genomics methods currently used as diagnostic tools for accurate discrimination between these two species. The ITS region of 82 strains was amplified and sequenced. The amplified fragments varied in size from 500 to 550 bp. Based on the sequence, seven SNPs were identified that separate L. garvieae from L. petauri. The 16S-23S rRNA ITS region has enough resolution to distinguish between closely related L. garvieae and L. petauri and it can be used as a diagnostic marker to quickly identify the pathogens in a lactococcosis outbreak.

Rapid Molecular Phenotypic Antimicrobial Susceptibility Test for Neisseria gonorrhoeae Based on Propidium Monoazide Viability PCR

Neisseria gonorrhoeae (NG) is an urgent threat to antimicrobial resistance (AMR) worldwide. NG has acquired rapid resistance to all previously recommended treatments, leaving ceftriaxone monotherapy as the first and last line of therapy for uncomplicated NG. The ability to rapidly determine susceptibility, which is currently nonexistent for NG, has been proposed as a strategy to preserve ceftriaxone by using alternative treatments. Herein, we used a DNA-intercalating dye in combination with NG-specific primers/probes to generate qPCR cycle threshold (Ct) values at different concentrations of 2 NG-relevant antimicrobials. Our proof-of-concept dual-antimicrobial logistic regression model based on the differential Ct measurements achieved an AUC of 0.93 with a categorical agreement for the susceptibility of 84.6%. When surveying the performance against each antimicrobial separately, the model predicted 90 and 75% susceptible and resistant strains, respectively, to ceftriaxone and 66.7 and 83.3% susceptible and resistant strains, respectively, to ciprofloxacin. We further validated the model against the individual replicates and determined the accuracy of the model in classifying susceptibility agnostic of the inoculum size. We demonstrated a novel PCR-based approach to determine phenotypic ciprofloxacin and ceftriaxone susceptibility information for NG with reasonable accuracy within 30 min, a significant improvement compared to the conventional method which could take multiple days.

Biofilm and wound healing: from bench to bedside

The bubbling community of microorganisms, consisting of diverse colonies encased in a self-produced protective matrix and playing an essential role in the persistence of infection and antimicrobial resistance, is often referred to as a biofilm. Although apparently indolent, the biofilm involves not only inanimate surfaces but also living tissue, making it truly ubiquitous. The mechanism of biofilm formation, its growth, and the development of resistance are ever-intriguing subjects and are yet to be completely deciphered. Although an abundance of studies in recent years has focused on the various ways to create potential anti-biofilm and antimicrobial therapeutics, a dearth of a clear standard of clinical practice remains, and therefore, there is essentially a need for translating laboratory research to novel bedside anti-biofilm strategies that can provide a better clinical outcome. Of significance, biofilm is responsible for faulty wound healing and wound chronicity. The experimental studies report the prevalence of biofilm in chronic wounds anywhere between 20 and 100%, which makes it a topic of significant concern in wound healing. The ongoing scientific endeavor to comprehensively understand the mechanism of biofilm interaction with wounds and generate standardized anti-biofilm measures which are reproducible in the clinical setting is the challenge of the hour. In this context of "more needs to be done", we aim to explore various effective and clinically meaningful methods currently available for biofilm management and how these tools can be translated into safe clinical practice.

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.

Performance Comparison Between Fourier-Transform Infrared Spectroscopy-based IR Biotyper and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for Strain Diversity

Background

Development of an accessible method to routinely evaluate the clonality of strains is needed in microbiology laboratories. We compared the discriminatory power of the Fourier-transform infrared (FTIR) spectroscopy-based IR Biotyper (Bruker Daltonics GmbH, Bremen, Germany) to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), using whole-genome sequencing (WGS) as the reference method.

Methods

Eighty-three extended-spectrum β-lactamase-producing Escherichia coli isolates were tested using WGS, MALDI-TOF MS, and IR Biotyper. Simpson's diversity index (SDI), a statistical analysis for testing the homogeneity of a dendrogram, and the adjusted Rand index (aRI) were used to compare the discriminatory ability between typing tests.

Results

The SDI (95% confidence interval) was 0.969 (0.952-0.985) for WGS, 0.865 (0.807-0.924) for MALDI-TOF MS, and 0.974 (0.965-0.983) for IR Biotyper. Compared with WGS, IR Biotyper showed compatible diversity, whereas MALDI-TOF MS did not. The concordance and aRI improved from 66.3% to 84.3% and from 0.173 to 0.538, respectively, for IR Biotyper versus MALDI-TOF MS with WGS as the reference method. IR Biotyper showed substantially improved performance in strain typing compared with MALDI-TOF MS.

Conclusions

IR Biotyper is useful for diversity analysis with improved discriminatory power over MALDI-TOF MS in comparison with WGS as a reference method. IR Biotyper is an accessible method to evaluate the clonality of strains and could be applied in epidemiological analysis during an outbreak of a health care facility, as well as for research on the transmission of resistant bacteria in community settings.

6-Bromoindirubin-3'-oxime derivatives are highly active colistin adjuvants against Klebsiella pneumoniae

Multidrug resistant (MDR) bacterial infections have become increasingly common, leading clinicians to rely on last-resort antibiotics such as colistin. However, the utility of colistin is becoming increasingly compromised as a result of increasing polymyxin resistance. Recently we discovered that derivatives of the eukaryotic kinase inhibitor meridianin D abrogate colistin resistance in several Gram-negative species. A subsequent screen of three commercial kinase inhibitor libraries led to the identification of several scaffolds that potentiate colistin activity, including 6-bromoindirubin-3'-oxime, which potently suppresses colistin resistance in Klebsiella pneumoniae. Herein we report the activity of a library of 6-bromoindirubin-3'-oxime analogs and identify four derivatives that show equal or increased colistin potentiation activity compared to the parent compound.

Clinical Implementation of Routine Whole-genome Sequencing for Hospital Infection Control of Multi-drug Resistant Pathogens

BACKGROUND

Prospective whole-genome sequencing (WGS)-based surveillance may be the optimal approach to rapidly identify transmission of multi-drug resistant (MDR) bacteria in the healthcare setting.

METHODS

We prospectively collected methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), carbapenem-resistant Acinetobacter baumannii (CRAB), extended-spectrum beta-lactamase (ESBL-E), and carbapenemase-producing Enterobacterales (CPE) isolated from blood cultures, sterile sites, or screening specimens across three large tertiary referral hospitals (2 adult, 1 paediatric) in Brisbane, Australia. WGS was used to determine in silico multi-locus sequence typing (MLST) and resistance gene profiling via a bespoke genomic analysis pipeline. Putative transmission events were identified by comparison of core genome single nucleotide polymorphisms (SNPs). Relevant clinical meta-data were combined with genomic analyses via customised automation, collated into hospital-specific reports regularly distributed to infection control teams.

RESULTS

Over 4 years (April 2017 to July 2021) 2660 isolates were sequenced. This included MDR gram-negative bacilli (n = 293 CPE, n = 1309 ESBL), MRSA (n = 620), and VRE (n = 433). A total of 379 clinical reports were issued. Core genome SNP data identified that 33% of isolates formed 76 distinct clusters. Of the 76 clusters, 43 were contained to the 3 target hospitals, suggesting ongoing transmission within the clinical environment. The remaining 33 clusters represented possible inter-hospital transmission events or strains circulating in the community. In 1 hospital, proven negligible transmission of non-multi-resistant MRSA enabled changes to infection control policy.

CONCLUSIONS

Implementation of routine WGS for MDR pathogens in clinical laboratories is feasible and can enable targeted infection prevention and control interventions.

Streptococcus pyogenes carriage acquisition, persistence and transmission dynamics within households in The Gambia (SpyCATS): protocol for a longitudinal household cohort study

Background Streptococcus pyogenes (StrepA) causes a significant burden of disease globally from superficial infections to invasive disease. It is responsible for over 500,000 deaths each year, predominantly in low- and middle-income countries (LMIC). Superficial StrepA infections of the skin and pharynx can lead to rheumatic heart disease, the largest cause of StrepA-related deaths in LMIC. StrepA can also asymptomatically colonise normal skin and the pharynx (carriage), potentially increasing infection risk. Streptococcus dysgalactiae subsp. equisimilis (SDSE) carriage is also common in LMIC and may interact with StrepA. This study aims to investigate StrepA and SDSE carriage and infection epidemiology, transmission dynamics and naturally acquired immunity within households in The Gambia. Methods A longitudinal household observational cohort study will be conducted over one year. 45 households will be recruited from the urban area of Sukuta, The Gambia, resulting in approximately 450 participants. Households will be visited monthly, and available participants will undergo oropharyngeal and normal skin swabbing. Incident cases of pharyngitis and pyoderma will be captured via active case reporting, with swabs taken from disease sites. Swabs will be cultured for the presence of group A, C and G beta-haemolytic streptococci. Isolates will undergo whole genome sequencing. At each visit, clinical, socio-demographic and social mixing data will be collected. Blood serum will be collected at baseline and final visit. Oral fluid and dried blood spot samples will be collected at each visit. Mucosal and serum anti-StrepA antibody responses will be measured. Outcome This study will report StrepA and SDSE clinical epidemiology, risk factors, transmission dynamics, and serological responses to carriage and infection. Detailed social mixing behaviour will be combined with phylogenetic relatedness to model the extent of transmission occurring withing and between households. The study will provide data to help meet global strategic StrepA research goals.

Achieving Ultrasensitive Chromogenic Probes for Rapid, Direct Detection of Carbapenemase-Producing Bacteria in Sputum

Carbapenemase-producing bacteria (CPB) stand as the most dangerous "superbugs" in the clinic. Rapid point-of-care (POC) detection of CPB in clinical samples is key to timely and effective infection management. We herein report the first ultrasensitive chromogenic probe that allows direct POC detection of CPB in clinical sputum samples at a sample-to-result time of less than 15 min. This chromogenic probe is modularly designed by conjugating the carbapenem core with a benzene derivative bearing an electronegativity-tunable substituent. Unexpectedly high sensitivity was achieved simply by choosing strong electron-withdrawing substituents, such as -N⁺(CH₃)₃, without resorting to complex molecular design. Through integrating the probes with a portable paper chip, 24 out of 80 clinical sputum samples from sepsis patients with lung infections were quickly diagnosed as CPB-positive, exhibiting 100% clinical sensitivity and specificity. This low-cost paper chip assay can be readily performed on-site, breaking through the dilemma of rapid CPB detection, especially in resource-limited settings.

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.

Clostridioides difficile in South American Camelids in Germany: First Insights into Molecular and Genetic Characteristics and Antimicrobial Resistance

Little is known about zoonotic pathogens and their antimicrobial resistance in South American camelids (SAC) in Germany including Clostridioides (C.) difficile. The aim of this study was to investigate prevalence, molecular characteristics and antimicrobial resistance of C. difficile in SAC. Composite SAC faecal samples were collected in 43 husbandries in Central Germany and cultured for C. difficile. Toxinotyping and ribotyping was done by PCR. Whole genome sequencing was performed with Illumina^® Miseq™. The genomes were screened for antimicrobial resistance determinants. Genetic relatedness of the isolates was investigated using core genome multi locus sequence typing (cgMLST) and single nucleotide polymorphism analysis. Antimicrobial susceptibility testing was done using the Etest^® method. Eight C. difficile isolates were recovered from seven farms. The isolates belonged to different PCR ribotypes. All isolates were toxinogenic. cgMLST revealed a cluster containing isolates recovered from different farms. Seven isolates showed similar resistance gene patterns. Different phenotypic resistance patterns were found. Agreement between phenotypic and genotypic resistance was identified only in some cases. Consequently, SAC may act as a reservoir for C. difficile. Thus, SAC may pose a risk regarding zoonotic transmission of toxinogenic, potentially human-pathogenic and resistant C. difficile isolates.

Whole-genome sequencing for surveillance of antimicrobial resistance in Ecuador: present and future implications

Whole-genome sequencing is becoming the gold standard for pathogen characterization and offers considerable advantages for understanding the evolution and dissemination of new determinants of antimicrobial resistance. Despite the benefits of whole-genome sequencing for pathogen characterization, implementation costs and lack of expertise may limit its use by public health laboratories. This article reviews the advantages of whole-genome sequencing for pathogen characterization and the current status of the use of whole-genome sequencing for antimicrobial resistance surveillance in Ecuador. A roadmap is suggested for including whole-genome sequencing for pathogen characterization based on the needs of the health reference institutions through alliances with Ecuadorian universities. Establishing a partnership between public health institutions and academia would be valuable for clinicians, policy-makers, and epidemiologists who could then take reasonable measures in those areas and establish a basis for adapting One Health strategies to tackle antimicrobial resistance in Ecuador.

An Automated Strategy to Handle Antigenic Variability in Immunisation Protocols, Part I: Nanopore Sequencing of Infectious Agent Variants

Infectious agents often challenge therapeutics, from antibiotics resistance to antigenic variability affecting inoculation measures. Over the last decades, genome sequencing arose as an important ally to address such challenges. In bacterial infection, whole-genome-sequencing (WGS) supports tracking pathogenic alterations affecting the human microbiome. In viral infection, the analysis of the relevant sequence of nucleotides helps with determining historical variants of a virus and elucidates details about infection clusters and their distribution. Additionally, genome sequencing is now an important step in inoculation protocols, isolating target genes to design more robust immunisation assays. Ultimately, genetic engineering has empowered repurposing at scale, allowing long-lasting repeating clinical trials to be automated within a much shorter time-frame, by adjusting existing protocols. This is particularly important during sanitary emergencies as the ones caused by the 2014 West African Ebola outbreak, the Zika virus rapid spread in both South and North America in 2015, followed by Asia in 2016, and the pandemic caused by the SARS-CoV-2, which has infected more than 187 million people and caused more than 4 million deaths, worldwide, as per July 2021 statistics. In this scenery, this chapter presents a novel fully automated strategy to handle antigenic variability in immunisation protocols. The methodology comprises of two major steps (1) nanopore sequencing of infectious agent variants - the focus is on the SARS-CoV-2 and its variants; followed by (2) mRNA vector design for immunotherapy. This chapter presents the nanopore sequencing step and Chapter 17 introduces a protocol for mRNA vector design.

Understanding the Interplay between Antimicrobial Resistance, Microplastics and Xenobiotic Contaminants: A Leap towards One Health?

According to the World Health Organization, the two major public health threats in the twenty-first century are antibiotic-resistant bacteria and antibiotic-resistant genes. The reason for the global prevalence and the constant increase of antibiotic-resistant bacteria is owed to the steady rise in overall antimicrobial consumption in several medical, domestic, agricultural, industrial, and veterinary applications, with consequent environmental release. These antibiotic residues may directly contaminate terrestrial and aquatic environments in which antibiotic-resistance genes are also present. Reports suggest that metal contamination is one of the main drivers of antimicrobial resistance (AMR). Moreover, the abundance of antibiotic-resistance genes is directly connected to the predominance of metal concentrations in the environment. In addition, microplastics have become a threat as emerging contaminants because of their ubiquitous presence, bio-inertness, toughness, danger to aquatic life, and human health implications. In the environment, microplastics and AMR are interconnected through biofilms, where genetic information (e.g., ARGs) is horizontally transferred between bacteria. From this perspective, we tried to summarize what is currently known on this topic and to propose a more effective One Health policy to tackle these threats.

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.

Human microbiome and microbiota identification for preventing and controlling healthcare-associated infections: A systematic review

Objective

This systematic review describes the role of the human microbiome and microbiota in healthcare-associated infections (HAIs). Studies on the microbiota of patients, healthcare environment (HE), medical equipment, or healthcare workers (HCW) and how it could be transmitted among the different subjects will be described in order to define alarming risk factors for HAIs spreading and to identify strategies for HAIs control or prevention.

Methods

This review was performed in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After retrieval in databases, identification, and screening of available records, 36 published studies were considered eligible and included in the review.

Results

A multifaceted approach is required and the analyses of the many factors related to human microbiota, which can influence HAIs onset, could be of paramount importance in their prevention and control. In this review, we will focus mainly on the localization, transmission, and prevention of ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) bacteria and Clostridium difficile which are the most common pathogens causing HAIs.

Conclusions

Healthcare workers' microbiota, patient's microbiota, environmental and medical equipment microbiota, ecosystem characteristics, ways of transmission, cleaning strategies, and the microbial resistome should be taken into account for future studies on more effective preventive and therapeutic strategies against HAIs.

Whole Genome Analyses Accurately Identify Neisseria spp. and Limit Taxonomic Ambiguity

Genome sequencing facilitates the study of bacterial taxonomy and allows the re-evaluation of the taxonomic relationships between species. Here, we aimed to analyze the draft genomes of four commensal Neisseria clinical isolates from the semen of infertile Lebanese men. To determine the phylogenetic relationships among these strains and other Neisseria spp. and to confirm their identity at the genomic level, we compared the genomes of these four isolates with the complete genome sequences of Neisseria gonorrhoeae and Neisseria meningitidis and the draft genomes of Neisseria flavescens, Neisseria perflava, Neisseria mucosa, and Neisseria macacae that are available in the NCBI Genbank database. Our findings revealed that the WGS analysis accurately identified and corroborated the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) species identities of the Neisseria isolates. The combination of three well-established genome-based taxonomic tools (in silico DNA-DNA Hybridization, Ortho Average Nucleotide identity, and pangenomic studies) proved to be relatively the best identification approach. Notably, we also discovered that some Neisseria strains that are deposited in databases contain many taxonomical errors. The latter is very important and must be addressed to prevent misdiagnosis and missing emerging etiologies. We also highlight the need for robust cut-offs to delineate the species using genomic tools.

Pathogenic strains of Shewanella putrefaciens contain plasmids that are absent in the probiotic strain Pdp11

Shewanella putrefaciens Pdp11 is a strain described as a probiotic for use in aquaculture. However, S. putrefaciens includes strains reported to be pathogenic or saprophytic to fish. Although the probiotic trait has been related to the presence of a group of genes in its genome, the existence of plasmids that could determine the probiotic or pathogenic character of this bacterium is unknown. In the present work, we searched for plasmids in several strains of S. putrefaciens that differ in their pathogenic and probiotic character. Under the different conditions tested, plasmids were only found in two of the five pathogenic strains, but not in the probiotic strain nor in the two saprophytic strains tested. Using a workflow integrating Sanger and Illumina reads, the complete consensus sequences of the plasmids were obtained. Plasmids differed in one ORF and encoded a putative replication initiator protein of the repB family, as well as proteins related to plasmid stability and a toxin-antitoxin system. Phylogenetic analysis showed some similarity to functional repB proteins of other Shewanella species. The implication of these plasmids in the probiotic or pathogenic nature of S. putrefaciens is discussed.

Antimicrobial susceptibility and multilocus sequence typing of Clostridium perfringens isolated from yaks in Qinghai-Tibet plateau, China

Clostridium perfringens (C. perfringens) is an opportunistic pathogen that cause necrotic enteritis, food poisoning and even death in animals. In this study, we explored the prevalence, antibiotic resistance and genetic diversity of Clostridium perfringens isolated from yak in the Qinghai-Tibet plateau, China. A total of 744 yak fecal samples were collected and assessed for toxin genes, antimicrobial susceptibility and multilocus sequence typing (MLST). Results indicated that 144 out of 744 (19.35%) yak fecal samples were tested to be positive for C. perfringens, 75% (n = 108, 108/144) were C. perfringens type A, 17.36% (n = 25, 25/144) were C. perfringens type C, 2.78% (n = 4, 4/144) were C. perfringens type D, and 4.86% (n = 7, 7/144) were C. perfringens type F. In addition, 2.78% (n = 4, 4/144) of the isolates were positive for cpb2 toxin gene. Antimicrobial susceptibility testing revealed that 98.61% (142/144) of the isolates showed multiple-antibiotic resistance. According to MLST and phylogenetic tree, 144 yak-derived C. perfringens isolates had an average of 12.95 alleles and could be divided into 89 sequence types (STs) and clustered in 11 clonal complexes (CCs). The most of isolates belong to type A with a considerable genetic diversity, having Simpson index up to 0.9754. MLST and phylogenetic analysis showed that the isolates under the same clade came from multiple regions. Cross-transmission among isolates and interconnectedness were observed in the genetic evolution. According to the study, the most of the isolates exhibited broad-spectrum antibacterial resistance, diverse alleles, and multiple lethal toxin genes of C. perfringens.

The New Precision Stewards?

The precision health era is likely to reduce and respond to antimicrobial resistance (AMR). Our stewardship and precision efforts share terminology, seeking to deliver the “right drug, at the right dose, at the right time.” Already, rapid diagnostic testing, phylogenetic surveillance, and real-time outbreak response provide just a few examples of molecular advances we dub “precision stewardship.” However, the AMR causal factors range from the molecular to that of global health policy. Mirroring the cross-sectoral nature of AMR science, the research addressing the ethical, legal and social implications (ELSI) of AMR ranges across academic scholarship. As the rise of AMR is accompanied by an escalating sense of its moral and social significance, what is needed is a parallel field of study. In this paper, we offer a gap analysis of this terrain, or an agenda for “the ELSI of precision stewardship.” In the first section, we discuss the accomplishments of a multi-decade U.S. national investment in ELSI research attending to the advances in human genetics. In the next section, we provide an overview of distinct ELSI topics pertinent to AMR. The distinctiveness of an ELSI agenda for precision stewardship suggests new opportunities for collaboration to build the stewardship teams of the future.

Molecular characterisation of Acinetobacter baumannii isolates from bloodstream infections in a tertiary-level hospital in South Africa

Acinetobacter baumannii is an opportunistic pathogen and causes various infections in patients. This study aimed to describe the clinical, epidemiological and molecular characteristics of A. baumannii isolated from BCs in patients at a tertiary-level hospital in South Africa. Ninety-six isolates from bloodstream infections were collected. Clinical characteristics of patients were recorded from patient files. Organism identification and AST was performed using automated systems. PCR screening for the mcr-1 to mcr-5 genes was done. To infer genetic relatedness, a dendrogram was constructed using MALDI-TOF MS. All colistin-resistant isolates (n = 9) were selected for WGS. The patients were divided into three groups, infants (<1 year; n = 54), paediatrics (1–18 years; n = 6) and adults (≥19 years; n = 36) with a median age of 13 days, 1 and 41 years respectively. Of the 96 A. baumannii bacteraemia cases, 96.9% (93/96) were healthcare-associated. The crude mortality rate at 30 days was 52.2% (48/92). The majority of the isolates were multidrug-resistant (MDR). All isolates were PCR-negative for the mcr-1 to mcr-5 genes. The majority of the isolates belonged to cluster 1 (62/96) according to the MALDI-TOF MS dendrogram. Colistin resistance was confirmed in nine A. baumannii isolates (9.4%). The colistin-resistant isolates belonged to sequence type (ST) 1 (5/6) and ST2 (1/6). The majority of ST1 isolates showed low SNP diversity (≤4 SNPs). All the colistin-resistant isolates were resistant to carbapenems, exhibited an XDR phenotype and harboured the bla_OXA–23 gene. The bla_NDM gene was only detected in ST1 colistin-resistant isolates (n = 5). The lpsB gene was detected in all colistin-resistant isolates as well as various efflux pump genes belonging to the RND, the MFS and the SMR families. The lipooligosaccharide OCL1 was detected in all colistin-resistant ST1 and ST2 isolates and the capsular polysaccharide KL3 and KL17 were detected in ST2 and ST1 respectively. This study demonstrated a 9.4% prevalence of colistin-resistant ST1 and ST2 A. baumannii in BC isolates. The detection of the lpsB gene indicates a potential threat and requires close prospective monitoring.

The role of the microbiology laboratory in the diagnosis of multidrug-resistant Gram-negative bacilli infections. The importance of the determination of resistance mechanisms

Early diagnosis and treatment has an important impact on the morbidity and mortality of infections caused by multidrug-resistant bacteria. Multidrug-resistant gram-negative bacilli (MR-GNB) constitute the main current threat in hospitals and especially in intensive care units (ICU). The role of the microbiology laboratory is essential in providing a rapid and effective response. This review updates the microbiology laboratory procedures for the rapid detection of BGN-MR and its resistance determinants. The role of the laboratory in the surveillance and control of outbreaks caused by these bacteria, including typing techniques, is also studied. The importance of providing standardized resistance maps that allow knowing the epidemiological situation of the different units is emphasized. Finally, the importance of effective communication systems for the transmission of results and decision making in the management of patients infected by BGN-MR is reviewed.

Potential of bacteriophage proteins as recognition molecules for pathogen detection

Bacterial pathogens are leading causes of infections with high mortality worldwide having a great impact on healthcare systems and the food industry. Gold standard methods for bacterial detection mainly rely on culture-based technologies and biochemical tests which are laborious and time-consuming. Regardless of several developments in existing methods, the goal of achieving high sensitivity and specificity, as well as a low detection limit, remains unaccomplished. In past years, various biorecognition elements, such as antibodies, enzymes, aptamers, or nucleic acids, have been widely used, being crucial for the pathogens detection in different complex matrices. However, these molecules are usually associated with high detection limits, demand laborious and costly production, and usually present cross-reactivity. (Bacterio)phage-encoded proteins, especially the receptor binding proteins (RBPs) and cell-wall binding domains (CBDs) of endolysins, are responsible for the phage binding to the bacterial surface receptors in different stages of the phage lytic cycle. Due to their remarkable properties, such as high specificity, sensitivity, stability, and ability to be easily engineered, they are appointed as excellent candidates to replace conventional recognition molecules, thereby contributing to the improvement of the detection methods. Moreover, they offer several possibilities of application in a variety of detection systems, such as magnetic, optical, and electrochemical. Herein we provide a review of phage-derived bacterial binding proteins, namely the RBPs and CBDs, with the prospect to be employed as recognition elements for bacteria. Moreover, we summarize and discuss the various existing methods based on these proteins for the detection of nosocomial and foodborne pathogens.

Resistance and Pathogenicity of Salmonella Thompson Isolated from Incubation End of a Poultry Farm

Simple Summary

Non-typhoid Salmonella is the general term of Salmonella other than typhoid and paratyphoid, which often causes foodborne gastroenteritis in humans, but some serotypes have been proved to be pathogenic to poultry. Salmonella Enterica and Salmonella Typhimurium are the common serotypes pathogenic to poultry and have been systematically studied, but other serotypes have rarely been studied. During Salmonella surveillance in farms, we discovered by chance that Salmonella Thompson, a common non-typhoid Salmonella, is also pathogenic to avian embryos. Therefore, this study aimed to explore antimicrobial resistance and pathogenicity of clinical S. Thompson. Firstly, we found that the core-genome multilocus sequence typing of 14 clinical S. Thompson was consistent with two strains of S. Thompson from humans in China. Secondly, the antimicrobial resistance gene analysis demonstrated that all strains carried the polymyxin resistance gene mcr-9, which had not appeared resistance phenotype. Meanwhile, many essential virulence genes were also found in each S. Thompson isolate. Finally, the bacterial inoculation experiment revealed that clinical S. Thompson was highly pathogenic to newborn chicks after yolk sac inoculation. This study suggests that Salmonella Thompson can circulate between humans and poultry farms and transmit drug resistance genes and demonstrated that Salmonella Thompson is highly pathogenic to chicks and should be guarded against in the hatching stage of poultry farms.

Abstract

Salmonella Thompson, an important foodborne pathogen, is rarely found to be pathogenic to poultry. Accidentally, S. Thompson was found to be pathogenic to embryos of white feather broiler at a poultry farm in China. Therefore, this study aimed to explore antimicrobial resistance and pathogenicity of clinical S. Thompson isolated from dead poultry embryos. The phylogenetic tree based on 16S rRNA and seven housekeeping genes showed that the 14 clinical S. Thompson were closely related. The core-genome multilocus sequence typing of 14 clinical S. Thompson based on whole-genome sequencing was cgST-12774, consistent with the only two strains of S. Thompson from humans in China as reported in the NCBI database. The antimicrobial resistance gene analysis demonstrated that all strains carried aac(6′)-Iaa and the polymyxin resistance gene mcr-9. Antimicrobial sensitivity tests for 18 antibiotics showed that S. Thompson isolates displayed resistance against streptomycin (100%), ampicillin (35.7%), and doxycycline (14.3%), but sensitivity to polymyxin B, proving that the mcr-9 gene had not appeared resistance phenotype. Virulence genes Salmonella pathogenicity island (SPI) SPI1-5, type I fimbriae gene (fimA), flagellar assembly genes (bcfC, flhD, fliA, fliC, fljB, flgK, and lpfC), and other virulence genes (iroN, pagC, and cigR) were found in each S. Thompson isolate. Additionally, the bacterial inoculation experiment with 1-day-old chicks revealed that clinical S. Thompson was highly pathogenic to newborn chicks after yolk sac inoculation. This study highlighted that the S. Thompson isolated from poultry embryos and the S. Thompson causing human foodborne diarrhea in some parts of China belong to the same cgMLST typology (cgST-12774) and showed the pathogenicity of this clinical S. Thompson to chicks.

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.

Simultaneously screening for methicillin-resistant Staphylococcus aureus and its susceptibility to potentiated penicillins

Introduction. We recently revealed that a significant proportion of clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates are susceptible to pencillins and clavulanic acid (potentiated penicillins), including widely available combinations such as co-amoxiclav. These isolates also showed increased susceptibility to oxacillin on Iso-Sensitest Agar (ISA).Hypothesis/Gap Statement. The increased susceptibility to oxacillin displayed on ISA by these MRSA isolates may be used to distinguish them from the resistant ones.Aim. We aimed to develop a method to simultaneously screen a S. aureus clinical isolate for its susceptibility to methicillin and potentiated penicillins.Methodology. A double-disc diffusion method using 10 µg cefoxitin and 1 µg oxacillin discs on ISA was developed and tested against a panel of 120 whole genome-sequenced MRSA isolates. The sensitivity of the method was compared with that of previously published genotypic and phenotypic methods. In addition, double-disc diffusion was performed for all isolates on Müller-Hinton agar (MHA) following the European Committee on Antimicrobial Susceptibility Testing (EUCAST) protocol.Results. All isolates (120/120) were reconfirmed to be phenotypically MRSA, as indicated by the result of cefoxitin disc diffusion testing. All isolates (40/40) that had a pencillins and clavulanic acid (Pen-Clav)-resistant genotype were not inhibited by oxacillin, while 77/80 (96.3 %) isolates that had a Pen-Clav-susceptible genotype were inhibited by oxacillin on ISA. The results also showed that the EUCAST method using MHA correctly identified all isolates as MRSA but failed to distinguish the Pen-Clav-susceptible isolates from the Pen-Clav-resistant isolates.Conclusions. This double-disc diffusion method using ISA could be used to accurately screen for clinical MRSA isolates and determine their susceptibility to Pen-Clav simultaneously, rapidly identifying MRSA infections that might be suitable for treatment with potentiated penicillins.

Genomic Diversity of Hospital-Acquired Infections Revealed through Prospective Whole-Genome Sequencing-Based Surveillance

Healthcare-associated infections (HAIs) cause mortality, morbidity, and waste of health care resources. HAIs are also an important driver of antimicrobial resistance, which is increasing around the world. Beginning in November 2016, we instituted an initiative to detect outbreaks of HAIs using prospective whole-genome sequencing-based surveillance of bacterial pathogens collected from hospitalized patients. Here, we describe the diversity of bacteria sampled from hospitalized patients at a single center, as revealed through systematic analysis of bacterial isolate genomes. We sequenced the genomes of 3,004 bacterial isolates from hospitalized patients collected over a 25-month period. We identified bacteria belonging to 97 distinct species, which were distributed among 14 groups of related species. Within these groups, isolates could be distinguished from one another by both average nucleotide identity (ANI) and principal-component analysis of accessory genes (PCA-A). Core genome genetic distances and rates of evolution varied among species, which has practical implications for defining shared ancestry during outbreaks and for our broader understanding of the origins of bacterial strains and species. Finally, antimicrobial resistance genes and putative mobile genetic elements were frequently observed, and our systematic analysis revealed patterns of occurrence across the different species sampled from our hospital. Overall, this study shows how understanding the population structure of diverse pathogens circulating in a single health care setting can improve the discriminatory power of genomic epidemiology studies and can help define the processes leading to strain and species differentiation. IMPORTANCE Hospitalized patients are at increased risk of becoming infected with antibiotic-resistant organisms. We used whole-genome sequencing to survey and compare over 3,000 clinical bacterial isolates collected from hospitalized patients at a large medical center over a 2-year period. We identified nearly 100 different bacterial species, which we divided into 14 different groups of related species. When we examined how genetic relatedness differed between species, we found that different species were likely evolving at different rates within our hospital. This is significant because the identification of bacterial outbreaks in the hospital currently relies on genetic similarity cutoffs, which are often applied uniformly across organisms. Finally, we found that antibiotic resistance genes and mobile genetic elements were abundant and were shared among the bacterial isolates we sampled. Overall, this study provides an in-depth view of the genomic diversity and evolutionary processes of bacteria sampled from hospitalized patients, as well as genetic similarity estimates that can inform hospital outbreak detection and prevention efforts.

Combining Traditional and Molecular Techniques Supports the Discovery of a Novel Legionella Species During Environmental Surveillance in a Healthcare Facility

Legionella surveillance plays a significant role not only to prevent the risk of infection but also to study the ecology of isolates, their characteristics, and how their prevalence changes in the environment. The difficulty in Legionella isolation, identification, and typing results in a low notification rate; therefore, human infection is still underestimated. In addition, during Legionella surveillance, the special attention given to Legionella pneumophila leads to an underestimation of the prevalence and risk of infection for other species. This study describes the workflow performed during environmental Legionella surveillance that resulted in the isolation of two strains, named 8cVS16 and 9fVS26, associated with the genus Legionella. Traditional and novel approaches such as standard culture technique, MALDI-TOF MS, gene sequencing, and whole-genome sequencing (WGS) analysis were combined to demonstrate that isolates belong to a novel species. The strain characteristics, the differences between macrophage infectivity potential (mip), RNA polymerase β subunit (rpoB), and reference gene sequences, the average nucleotide identity (ANI) of 90.4%, and the DNA–DNA digital hybridization (dDDH) analysis of 43% demonstrate that these isolates belong to a new Legionella species. The finding suggests that, during the culture technique, special attention should be paid to the characteristics of the isolates that are less associated with the Legionella genus in order to investigate the differences found using more sensitive methods. The characterization of the two newly discovered isolates based on morphological, biochemical, and microscopic characteristics is currently underway and will be described in another future study.

Comprehensive approaches for the detection of Burkholderia pseudomallei and diagnosis of melioidosis in human and environmental samples

Melioidosis is endemic in Southeast Asia and northern Australia. The causative agent of melioidosis is a Gram-negative bacterium, Burkholderia pseudomallei. Its invasion can be fatal if melioidosis is not treated promptly. It is intrinsically resistant to a variety of antibiotics. In this paper, we present a comprehensive overview of the current trends on melioidosis cases, treatments, B. pseudomallei virulence factors, and molecular techniques to detect the bacterium from different samples. The clinical and microbial diagnosis methods of identification and detection of B. pseudomallei are commonly used for the rapid diagnosis and typing of strains, such as polymerase chain reaction or multi-locus sequence typing. The genotyping strategies and techniques have been constantly evolving to identify genomic loci linked to or associated with this human disease. More research strategies for detecting and controlling melioidosis should be encouraged and conducted to understand the current situation. In conclusion, we review existing diagnostic methodologies for melioidosis detection and provide insights on prospective diagnostic methods for the bacterium.

Assembly and Comparison of Ca. Neoehrlichia mikurensis Genomes

Ca. Neoehrlichia mikurensis is widely prevalent in I. ricinus across Europe and has been associated with human disease. However, diagnostic modalities are limited, and much is still unknown about its biology. Here, we present the first complete Ca. Neoehrlichia mikurensis genomes directly derived from wildlife reservoir host tissues, using both long- and short-read sequencing technologies. This pragmatic approach provides an alternative to obtaining sufficient material from clinical cases, a difficult task for emerging infectious diseases, and to expensive and challenging bacterial isolation and culture methods. Both genomes exhibit a larger chromosome than the currently available Ca. Neoehrlichia mikurensis genomes and expand the ability to find new targets for the development of supportive laboratory diagnostics in the future. Moreover, this method could be utilized for other tick-borne pathogens that are difficult to culture.

Systems biology approach to functionally assess the Clostridioides difficile pangenome reveals genetic diversity with discriminatory power

SignificanceClostridioides difficile infections are the most common source of hospital-acquired infections and are responsible for an extensive burden on the health care system. Strains of the C. difficile species comprise diverse lineages and demonstrate genome variability, with advantageous trait acquisition driving the emergence of endemic lineages. Here, we present a systems biology analysis of C. difficile that evaluates strain-specific genotypes and phenotypes to investigate the overall diversity of the species. We develop a strain typing method based on similarity of accessory genomes to identify and contextualize genetic loci capable of discriminating between strain groups.

Association of human gut microbiota with rare diseases: A close peep through

The human body harbors approximately 1014 cells belonging to a diverse group of microorganisms. Bacteria outnumbers protozoa, fungi and viruses inhabiting our gastrointestinal tract (GIT), commonly referred to as the "human gut microbiome". Dysbiosis occurs when the balanced relationship between the host and the gut microbiota is disrupted, altering the usual microbial population there. This increases the susceptibility of the host to pathogens, and chances of its morbidity. It is due to the fact that the gut microbiome plays an important role in human health; it influences the progression of conditions varying from colorectal cancer to GIT disorders linked with the nervous system, autoimmunity, metabolism and inheritance. A rare disease is a lethal and persistent condition affecting 2-3 people per 5,000 populaces. This review article intends to discuss such rare neurological, autoimmune, cardio-metabolic and genetic disorders of man, focusing on the fundamental mechanism that links them with their gut microbiome. Ten rare diseases, including Pediatric Crohn's disease (PCD), Lichen planus (LP), Hypophosphatasia (HPP), Discitis, Cogan's syndrome, Chancroid disease, Sennetsu fever, Acute cholecystitis (AC), Grave's disease (GD) and Tropical sprue (TS) stands to highlight as key examples, along with personalized therapeutics meant for them. This medicinal approach addresses the individual's genetic and genomic pathography, and tackles the illness with specific and effective treatments.

Whole genome sequencing of cyanobacterium Nostoc sp. CCCryo 231-06 using microfluidic single cell technology

The Nostoc sp. strain CCCryo 231-06 is a cyanobacterial strain capable of surviving under extreme conditions and thus is of great interest for the astrobiology community. The knowledge of its complete genome sequence would serve as a guide for further studies. However, a major concern has been placed on the effects of contamination on the quality of sequencing data without a reference genome. Here, we report the use of microfluidic technology combined with single cell sequencing and de novo assembly to minimize the contamination and recover the complete genome of the Nostoc strain CCCryo 231-06 with high quality. 100% of the whole genome was recovered with all contaminants removed and a strongly supported phylogenetic tree. The data reported can be useful for comparative genomics for phylogenetic and taxonomic studies. The method used in this work can be applied to studies that require high-quality assemblies of genomes of unknown microorganisms.

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This work uses a microfluidic platform for Nostoc single cell sequencing

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This technology provides minimal contamination in single cell sequencing

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Complete genome of the Nostoc strain CCCryo 231-06 was recovered with high quality

Benchmarking the topological accuracy of bacterial phylogenomic workflows using in silico evolution

Phylogenetic analyses are widely used in microbiological research, for example to trace the progression of bacterial outbreaks based on whole-genome sequencing data. In practice, multiple analysis steps such as de novo assembly, alignment and phylogenetic inference are combined to form phylogenetic workflows. Comprehensive benchmarking of the accuracy of complete phylogenetic workflows is lacking. To benchmark different phylogenetic workflows, we simulated bacterial evolution under a wide range of evolutionary models, varying the relative rates of substitution, insertion, deletion, gene duplication, gene loss and lateral gene transfer events. The generated datasets corresponded to a genetic diversity usually observed within bacterial species (≥95 % average nucleotide identity). We replicated each simulation three times to assess replicability. In total, we benchmarked 19 distinct phylogenetic workflows using 8 different simulated datasets. We found that recently developed k-mer alignment methods such as kSNP and ska achieve similar accuracy as reference mapping. The high accuracy of k-mer alignment methods can be explained by the large fractions of genomes these methods can align, relative to other approaches. We also found that the choice of de novo assembly algorithm influences the accuracy of phylogenetic reconstruction, with workflows employing SPAdes or skesa outperforming those employing Velvet. Finally, we found that the results of phylogenetic benchmarking are highly variable between replicates. We conclude that for phylogenomic reconstruction, k-mer alignment methods are relevant alternatives to reference mapping at the species level, especially in the absence of suitable reference genomes. We show de novo genome assembly accuracy to be an underappreciated parameter required for accurate phylogenomic reconstruction.

Monitoring microbial communities in intensive care units over one year in China

Healthcare-associated infections (HAIs) seriously threaten patient health in intensive care units (ICUs). Profiling the microbial composition and diversity in ICU is important to prevent HAI-related spreading. Given that microbial communities vary across different environments, the time-scale characteristics of pathogens in ICUs have not been explored in China. In our study, to study the bacterial communities of two different ICUs in China, we proceeded dynamic monitoring using 16S rRNA sequencing for a whole year among the bed sheets, bed rails, shared pulse oximeters, bedside lockers, nurses' hands, floor, and carts. Our results showed that the microbial composition significantly changed within months. Significant differences in alpha and beta diversities were also observed among the 12 sampling months in each ICU. Additionally, we found the persistence of several HAI-related bacteria, including Acinetobacter, Pseudomonas, Staphylococcus, Escherichia, and Enterococcus. Source tracking analysis showed that most bacteria in both ICUs came from buildings or human skin. With deep investigations of hospital microbial surveillance on a long-term time-scale, we hope that these results will provide constructive guidelines to prevent the spread of HAIs in ICUs.

One Day in Denmark: Nationwide point-prevalence survey of human bacterial isolates and comparison of classical and whole-genome sequence-based species identification methods

Objectives

Implementing whole-genome sequencing (WGS) technologies in clinical microbiology laboratories can increase the amount and quality of information available for healthcare practitioners. In this study, we analysed the applicability of this method and determined the distribution of bacterial species processed in clinical settings in Denmark.

Methods

We performed a point-prevalence study of all bacterial isolates (n = 2,009) processed and reported in the Clinical Microbiology Laboratories in Denmark in one day in January 2018. We compared species identification as performed by classical methods (MALDI-TOF) and by bioinformatics analysis (KmerFinder and rMLST) of WGS (Illumina NextSeq) data. We compared the national point-prevalence of bacterial isolates observed in clinical settings with the research attention given to those same genera in scientific literature.

Results

The most prevalent bacterium was Escherichia coli isolated from urine (n = 646), followed by Staphylococcus spp. from skin or soft tissues (n = 197). The distribution of bacterial species throughout the country was not homogeneous. We observed concordance of species identification for all methods in 95.7% (n = 1,919) of isolates, furthermore obtaining concordance for 99.7% (n = 1,999) at genus level. The number of scientific publications in the country did not correlate with the number of bacterial isolates of each genera analysed in this study.

Conclusions

WGS technologies have the potential to be applied in clinical settings for routine diagnostics purposes. This study also showed that bioinformatics databases should be continuously improved and results from local point-prevalence surveys should not be applied at national levels without previously determining possible regional variations.

Isolation and characterization of Escherichia albertii originated from the broiler farms in Mississippi and Alabama

Escherichia albertii is an emerging foodborne enteropathogen with increasing outbreaks worldwide, particularly in Japan recently. However, major features of this zoonotic pathogen, such as prevalence, virulence, and antibiotic resistance (AR), still remain under characterized. In a recent pilot study, we reported isolation of E. albertii from a chicken farm in Tennessee, suggesting chicken is an important reservoir for E. albertii. In this large-scale study, we examined prevalence of E. albertii in 9 farms in Mississippi and Alabama. Of a total of 270 cloacal swabs (30 per farm), 43 were PCR positive and 12 E. albertii strains were isolated with different isolation rates in individual farms ranging from 0 to 23.3 %. Both PFGE and whole genome analysis showed the E. albertii from different farms were phylogenetically distant, but those from the same farm displayed clonal relationships. Consistently, the antibiogram, AR gene profiles, and plasmid replicon types were similar across the strains in the same farm. Notably, 9 of the 12 E. albertii strains displayed multidrug resistance; one strain was even resistant to imipenem, a clinically important carbapenem antibiotic. In addition, comparative genomics analysis showed that two chicken E. albertii clusters displayed very close evolutionary relationships and similar virulence gene profiles to human E. albertii strains. In vitro growth assay demonstrated that the anti-enterobactin antibodies could dramatically inhibit the growth of two representative chicken E. albertii, supporting the feasibility of the novel enterobactin-based immune intervention for controlling this emerging pathogen. Taken together, the findings from this study further indicated chickens as an important reservoir for E. albertii in the U.S., highlighting the need to prevent and control E. albertii in poultry production.

Optimized analysis parameters of variant calling for whole genome-based phylogeny of Mycobacteroides abscessus

Whole-genome sequence (WGS) analysis provides the best resolution for reconstructing bacterial phylogeny. However, the resulting tree could vary according to parameters used in the WGS pipeline, making it difficult to compare results across multiple studies. This study compares effects on phylogenies when applying different parameter stringencies. We used as the study model to optimize parameters strains of Mycobacteroides abscessus serially isolated at various intervals, isolates known to represent persistent infection (PI) cases or re-infection (RI) cases and isolates from different subspecies. Un-optimized parameters with low stringency provided an excessive number of SNPs (823) compared to the optimized setting (3 SNPs) between paired strains isolated 1 day apart from PI cases, discordant tree topology and misclassification of subspecies and of instances of RI. We demonstrated that using high-quality variants provides more accuracy for recognizing serial isolates of the same clone versus different clones and for phylogenetic analysis of M. abscessus. Our approach might be used as a model for analyses requiring phylogenetic reconstruction of other bacteria.

Development of Single Nucleotide Polymorphism (SNP)-Based Triplex PCR Marker for Serotype-Specific Escherichia coli Detection

Single-nucleotide polymorphisms (SNPs) are one of the most common forms of genetic variation and as such are powerful tools for the identification of bacterial strains, their genetic diversity, phylogenetic analysis, and outbreak surveillance. In this study, we used 15 sets of SNP-containing primers to amplify and sequence the target Escherichia coli. Based on the combination of the 15-sequence primer sets, each SNP site encompassing forward and reverse primer sequences (620–919 bp) were aligned and an SNP-based marker was designed. Each SNP marker exists in at least two SNP sites at the 3′ end of each primer; one natural and the other artificially created by transition or transversion mutation. Thus, 12 sets of SNP primers (225–488 bp) were developed for validation by amplifying the target E. coli. Finally, a temperature gradient triplex PCR kit was designed to detect target E. coli strains. The selected primers were amplified in three genes (ileS, thrB, and polB), with fragment sizes of 401, 337, and 232 bp for E. coli O157:H7, E. coli, and E. coli O145:H28, respectively. This allele-specific SNP-based triplex primer assay provides serotype-specific detection of E. coli strains in one reaction tube. The developed marker would be used to diagnose, investigate, and control food-borne E. coli outbreaks.

Exploring the predictive capability of advanced machine learning in identifying severe disease phenotype in Salmonella enterica

The past few years have seen a significant increase in availability of whole genome sequencing information, allowing for its incorporation in predictive modeling for foodborne pathogens to account for inter- and intra-species differences in their virulence. However, this is hindered by the inability of traditional statistical methods to analyze such large amounts of data compared to the number of observations/isolates. In this study, we have explored the applicability of machine learning (ML) models to predict the disease outcome, while identifying features that exert a significant effect on the prediction. This study was conducted on Salmonella enterica, a major foodborne pathogen with considerable inter- and intra-serovar variation. WGS of isolates obtained from various sources (i.e., human, chicken, and swine) were used as input in four machine learning models (logistic regression with ridge, random forest, support vector machine, and AdaBoost) to classify isolates based on disease severity (extraintestinal vs. gastrointestinal) in the host. The predictive performances of all models were tested with and without Elastic Net regularization to combat dimensionality issues. Elastic Net-regularized logistic regression model showed the best area under the receiver operating characteristic curve (AUC-ROC; 0.86) and outcome prediction accuracy (0.76). Additionally, genes coding for transcriptional regulation, acidic, oxidative, and anaerobic stress response, and antibiotic resistance were found to be significant predictors of disease severity. These genes, which were significantly associated with each outcome, could possibly be input in amended, gene-expression-specific predictive models to estimate virulence pattern-specific effect of Salmonella and other foodborne pathogens on human health.