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.

Whole-Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection.

BACKGROUND: Most hospitals use traditional infection prevention (IP) methods for outbreak detection. We developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning (ML) of the electronic health record (EHR) to identify undetected outbreaks and the responsible transmission routes, respectively. METHODS: We performed WGS surveillance of healthcare-associated bacterial pathogens from November 2016 to November 2018. EHR ML was used to identify the transmission routes for WGS-detected outbreaks, which were investigated by an IP expert. Potential infections prevented were estimated and compared with traditional IP practice during the same period. RESULTS: Of 3165 isolates, there were 2752 unique patient isolates in 99 clusters involving 297 (10.8%) patient isolates identified by WGS; clusters ranged from 2-14 patients. At least 1 transmission route was detected for 65.7% of clusters. During the same time, traditional IP investigation prompted WGS for 15 suspected outbreaks involving 133 patients, for which transmission events were identified for 5 (3.8%). If EDS-HAT had been running in real time, 25-63 transmissions could have been prevented. EDS-HAT was found to be cost-saving and more effective than traditional IP practice, with overall savings of $192 408-$692 532. CONCLUSIONS: EDS-HAT detected multiple outbreaks not identified using traditional IP methods, correctly identified the transmission routes for most outbreaks, and would save the hospital substantial costs. Traditional IP practice misidentified outbreaks for which transmission did not occur. WGS surveillance combined with EHR ML has the potential to save costs and enhance patient safety.

Outbreak of Pseudomonas aeruginosa Infections from a Contaminated Gastroscope Detected by Whole Genome Sequencing Surveillance.

BACKGROUND: Traditional methods of outbreak investigations utilize reactive whole genome sequencing (WGS) to confirm or refute the outbreak. We have implemented WGS surveillance and a machine learning (ML) algorithm for the electronic health record (EHR) to retrospectively detect previously unidentified outbreaks and to determine the responsible transmission routes. METHODS: We performed WGS surveillance to identify and characterize clusters of genetically-related Pseudomonas aeruginosa infections during a 24-month period. ML of the EHR was used to identify potential transmission routes. A manual review of the EHR was performed by an infection preventionist to determine the most likely route and results were compared to the ML algorithm. RESULTS: We identified a cluster of 6 genetically related P. aeruginosa cases that occurred during a 7-month period. The ML algorithm identified gastroscopy as a potential transmission route for 4 of the 6 patients. Manual EHR review confirmed gastroscopy as the most likely route for 5 patients. This transmission route was confirmed by identification of a genetically-related P. aeruginosa incidentally cultured from a gastroscope used on 4of the 5 patients. Three infections, 2 of which were blood stream infections, could have been prevented if the ML algorithm had been running in real-time. CONCLUSIONS: WGS surveillance combined with a ML algorithm of the EHR identified a previously undetected outbreak of gastroscope-associated P. aeruginosa infections. These results underscore the value of WGS surveillance and ML of the EHR for enhancing outbreak detection in hospitals and preventing serious infections.

Transmission Dynamics and Microevolution of Neisseria meningitidis During Carriage and Invasive Disease in High School Students in Georgia and Maryland, 2006-2007.

BACKGROUND: The mechanisms by which Neisseria meningitidis cause persistent human carriage and transition from carriage to invasive disease have not been fully elucidated. METHODS: Georgia and Maryland high school students were sampled for pharyngeal carriage of N. meningitidis during the 2006-2007 school year. A total of 321 isolates from 188 carriers and all 67 invasive disease isolates collected during the same time and from the same geographic region underwent whole-genome sequencing. Core-genome multilocus sequence typing was used to compare allelic profiles, and direct read mapping was used to study strain evolution. RESULTS: Among 188 N. meningitidis culture-positive students, 98 (52.1%) were N. meningitidis culture positive at 2 or 3 samplings. Most students who were positive at >1 sampling (98%) had persistence of a single strain. More than a third of students carried isolates that were highly genetically related to isolates from other students in the same school, and occasional transmission within the same county was also evident. The major pilin subunit gene, pilE, was the most variable gene, and no carrier had identical pilE sequences at different time points. CONCLUSION: We found strong evidence of local meningococcal transmission at both the school and county levels. Allelic variation within genes encoding bacterial surface structures, particularly pilE, was common.

Outbreak of Vancomycin-resistant Enterococcus faecium in Interventional Radiology: Detection Through Whole-genome Sequencing-based Surveillance.

BACKGROUND: Vancomycin-resistant enterococci (VRE) are a major cause of hospital-acquired infections. The risk of infection from interventional radiology (IR) procedures is not well documented. Whole-genome sequencing (WGS) surveillance of clinical bacterial isolates among hospitalized patients can identify previously unrecognized outbreaks. METHODS: We analyzed WGS surveillance data from November 2016 to November 2017 for evidence of VRE transmission. A previously unrecognized cluster of 10 genetically related VRE (Enterococcus faecium) infections was discovered. Electronic health record review identified IR procedures as a potential source. An outbreak investigation was conducted. RESULTS: Of the 10 outbreak patients, 9 had undergone an IR procedure with intravenous (IV) contrast ≤22 days before infection. In a matched case-control study, preceding IR procedure and IR procedure with contrast were associated with VRE infection (matched odds ratio [MOR], 16.72; 95% confidence interval [CI], 2.01 to 138.73; P = .009 and MOR, 39.35; 95% CI, 7.85 to infinity; P < .001, respectively). Investigation of IR practices and review of the manufacturer's training video revealed sterility breaches in contrast preparation. Our investigation also supported possible transmission from an IR technician. Infection prevention interventions were implemented, and no further IR-associated VRE transmissions have been observed. CONCLUSIONS: A prolonged outbreak of VRE infections related to IR procedures with IV contrast resulted from nonsterile preparation of injectable contrast. The fact that our VRE outbreak was discovered through WGS surveillance and the manufacturer's training video that demonstrated nonsterile technique raise the possibility that infections following invasive IR procedures may be more common than previously recognized.

Evolution of Outbreak-Causing Carbapenem-Resistant Klebsiella pneumoniae ST258 at a Tertiary Care Hospital over 8 Years.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) strains belonging to sequence type 258 (ST258) are frequent causes of hospital-associated outbreaks and are a major contributor to the spread of carbapenemases. This genetic lineage emerged several decades ago and remains a major global health care challenge. In this study, genomic epidemiology was used to investigate the emergence, evolution, and persistence of ST258 carbapenem-resistant K. pneumoniae outbreak-causing lineages at a large tertiary care hospital over 8 years. A time-based phylogenetic analysis of 136 ST258 isolates demonstrated the succession of multiple genetically distinct ST258 sublineages over the 8-year period. Ongoing genomic surveillance identified the emergence and persistence of several distinct clonal ST258 populations. Patterns of multidrug resistance determinants and plasmid replicons were consistent with continued evolution and persistence of these populations. Five ST258 outbreaks were documented, including three that were caused by the same clonal lineage. Mutations in genes encoding effectors of biofilm production and iron acquisition were identified among persistent clones. Two emergent lineages bearing K. pneumoniae integrative conjugative element 10 (ICEKp10) and harboring yersiniabactin and colibactin virulence factors were identified. The results show how distinct ST258 subpopulations have evolved and persisted within the same hospital over nearly a decade.IMPORTANCE The carbapenem class of antibiotics is invaluable for the treatment of selected multidrug-resistant Gram-negative pathogens. The continued transmission of carbapenem-resistant bacteria such as ST258 K. pneumoniae is of serious global public health concern, as treatment options for these infections are limited. This genomic epidemiologic investigation traced the natural history of ST258 K. pneumoniae in a single health care setting over nearly a decade. We found that distinct ST258 subpopulations have caused both device-associated and ward-associated outbreaks, and some of these populations remain endemic within our hospital to the present day. The finding of virulence determinants among emergent ST258 clones supports the idea of convergent evolution of drug-resistant and virulent CRKP strains and highlights the need for continued surveillance, prevention, and control efforts to address emergent and evolving ST258 populations in the health care setting.

Use of online tools for antimicrobial resistance prediction by whole-genome sequencing in methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE).

OBJECTIVES: The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly available web-based AMR databases, whole-genome sequencing (WGS) offers the capacity for rapid detection of AMR genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility test results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) clinical isolates using publicly available tools and databases. METHODS: Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. The AMR gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between the WGS-predicted resistance profile and phenotypic susceptibility as well as the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for each antibiotic/organism combination, using the phenotypic results as gold standard. RESULTS: Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3%, with a sensitivity, specificity, PPV and NPV of 98.7% (95% CI 97.2-99.5%), 99.6% (95% CI 98.8-99.9%), 99.3% (95% CI 98.0-99.8%) and 99.2% (95% CI 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4%, sensitivity to 99.3% (95% CI 98.2-99.8%) and NPV to 99.4% (95% CI 98.4-99.8%). CONCLUSION: WGS can be used as a reliable predicator of phenotypic resistance both for MRSA and VRE using readily available online tools.

Neisseria meningitidis disease-associated clones in Amazonas State, Brazil.

BACKGROUND: The aim of this study is to describe the molecular epidemiology of Neisseria meningitidis invasive disease before the introduction of serogroup C conjugate vaccine in Amazonas State in 2010. METHODS: Meningococcal disease reported cases were investigated in Amazonas State during the period 2000-2010. N. meningitidis isolates (n = 196) recovered from patients were genotyped by multilocus sequence typing (MLST) and sequencing of porB, porA, fetA, fHbp and penA. Antimicrobial susceptibility was determined using E-test. RESULTS: In the study period, 948 cases were reported; the incidence was 2.8 for the entire state and 4.8 per 100,000 in the capital of Manaus. Most meningococcal disease was caused by N. meningitidis belonging to ST-32 (72%; 141/196) or ST-103 (21%; 41/196) clonal complexes. Capsular switching (B→C) was suggested within clonal complex (cc) 32. There were 6 (3%; 6/196) strains with intermediate susceptibility to penicillin and a single strain was resistant to rifampicin. Since 2007, serogroup C strains belonging to the cc103 have predominated and case-fatality has increased. CONCLUSION: We demonstrate a high rate of meningococcal disease in Amazonas State, where, like other parts of Brazil, serogroup C replaced serogroup B during 2000s. These data serve as a baseline to measure impact of serogroup C conjugate vaccine introduction in 2010. This study emphasizes the need for enhanced surveillance to monitor changes in meningococcal disease trends following the introduction of meningococcal vaccines.

Draft Genome Sequences of Four Hospital-Associated Pseudomonas putida Isolates.

We present here the draft genome sequences of four Pseudomonas putida isolates belonging to a single clone suspected for nosocomial transmission between patients and a bronchoscope in a tertiary hospital. The four genome sequences belong to a single lineage but contain differences in their mobile genetic elements.

Brain region-specific expression of MeCP2 isoforms correlates with DNA methylation within Mecp2 regulatory elements.

MeCP2 is a critical epigenetic regulator in brain and its abnormal expression or compromised function leads to a spectrum of neurological disorders including Rett Syndrome and autism. Altered expression of the two MeCP2 isoforms, MeCP2E1 and MeCP2E2 has been implicated in neurological complications. However, expression, regulation and functions of the two isoforms are largely uncharacterized. Previously, we showed the role of MeCP2E1 in neuronal maturation and reported MeCP2E1 as the major protein isoform in the adult mouse brain, embryonic neurons and astrocytes. Recently, we showed that DNA methylation at the regulatory elements (REs) within the Mecp2 promoter and intron 1 impact the expression of Mecp2 isoforms in differentiating neural stem cells. This current study is aimed for a comparative analysis of temporal, regional and cell type-specific expression of MeCP2 isoforms in the developing and adult mouse brain. MeCP2E2 displayed a later expression onset than MeCP2E1 during mouse brain development. In the adult female and male brain hippocampus, both MeCP2 isoforms were detected in neurons, astrocytes and oligodendrocytes. Furthermore, MeCP2E1 expression was relatively uniform in different brain regions (olfactory bulb, striatum, cortex, hippocampus, thalamus, brainstem and cerebellum), whereas MeCP2E2 showed differential enrichment in these brain regions. Both MeCP2 isoforms showed relatively similar distribution in these brain regions, except for cerebellum. Lastly, a preferential correlation was observed between DNA methylation at specific CpG dinucleotides within the REs and Mecp2 isoform-specific expression in these brain regions. Taken together, we show that MeCP2 isoforms display differential expression patterns during brain development and in adult mouse brain regions. DNA methylation patterns at the Mecp2 REs may impact this differential expression of Mecp2/MeCP2 isoforms in brain regions. Our results significantly contribute towards characterizing the expression profiles of Mecp2/MeCP2 isoforms and thereby provide insights on the potential role of MeCP2 isoforms in the developing and adult brain.

MeCP2-Related Diseases and Animal Models.

The role of epigenetics in human disease has become an area of increased research interest. Collaborative efforts from scientists and clinicians have led to a better understanding of the molecular mechanisms by which epigenetic regulation is involved in the pathogenesis of many human diseases. Several neurological and non-neurological disorders are associated with mutations in genes that encode for epigenetic factors. One of the most studied proteins that impacts human disease and is associated with deregulation of epigenetic processes is Methyl CpG binding protein 2 (MeCP2). MeCP2 is an epigenetic regulator that modulates gene expression by translating epigenetic DNA methylation marks into appropriate cellular responses. In order to highlight the importance of epigenetics to development and disease, we will discuss how MeCP2 emerges as a key epigenetic player in human neurodevelopmental, neurological, and non-neurological disorders. We will review our current knowledge on MeCP2-related diseases, including Rett Syndrome, Angelman Syndrome, Fetal Alcohol Spectrum Disorder, Hirschsprung disease, and Cancer. Additionally, we will briefly discuss about the existing MeCP2 animal models that have been generated for a better understanding of how MeCP2 impacts certain human diseases.

Novel MeCP2 isoform-specific antibody reveals the endogenous MeCP2E1 expression in murine brain, primary neurons and astrocytes.

Rett Syndrome (RTT) is a severe neurological disorder in young females, and is caused by mutations in the X-linked MECP2 gene. MECP2/Mecp2 gene encodes for two protein isoforms; MeCP2E1 and MeCP2E2 that are identical except for the N-terminus region of the protein. In brain, MECP2E1 transcripts are 10X higher, and MeCP2E1 is suggested to be the relevant isoform for RTT. However, due to the unavailability of MeCP2 isoform-specific antibodies, the endogenous expression pattern of MeCP2E1 is unknown. To gain insight into the expression of MeCP2E1 in brain, we have developed an anti-MeCP2E1 antibody and validated its specificity in cells exogenously expressing individual MeCP2 isoforms. This antibody does not show any cross-reactivity with MeCP2E2 and detects endogenous MeCP2E1 in mice brain, with no signal in Mecp2(tm1.1Bird) y/- null mice. Additionally, we show the endogenous MeCP2E1 expression throughout different brain regions in adult mice, and demonstrate its highest expression in the brain cortex. Our results also indicate that MeCP2E1 is highly expressed in primary neurons, as compared to primary astrocytes. This is the first report of the endogenous MeCP2E1 expression at the protein levels, providing novel avenues for understanding different aspects of MeCP2 function.