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Klebsiella pneumoniae has been classified into two types, classical K. pneumoniae (cKP) and hypervirulent K. pneumoniae (hvKP). cKP isolates are highly diverse and important causes of nosocomial infections; they include globally disseminated antibiotic-resistant clones. hvKP isolates are sensitive to most antibiotics but are highly virulent, causing community-acquired infections in healthy individuals. The virulence phenotype of hvKP is associated with pathogenicity loci responsible for siderophore and hypermucoid capsule production. Recently, convergent strains of K. pneumoniae , which possess features of both cKP and hvKP, have emerged and are cause of much concern. Here, we screen the genomes of 2,608 multidrug-resistant K. pneumoniae isolates from the United States and identify 47 convergent isolates. We perform phenotypic and genomic characterization of 12 representative isolates. These 12 convergent isolates contain a variety of antimicrobial resistance plasmids and virulence plasmids. Most convergent isolates contain aerobactin biosynthesis genes and produce more siderophores than cKP isolates but not more capsule. Unexpectedly, only 1 of the 12 tested convergent isolates has a level of virulence consistent with hvKP isolates in a murine pneumonia model. These findings suggest that additional studies should be performed to clarify whether convergent strains are indeed more virulent than cKP in mouse and human infections. Convergent strains, those containing characteristics of both multidrug-resistant & hypervirulent Klebsiella pneumoniae , are a global threat to public health. In this work, authors analyse convergent isolates from the United States and reveal unexpectantly low virulence.

Klebsiella pneumoniae is a serious human pathogen associated with resistance to multiple antibiotics and high mortality. K. variicola and K. quasipneumoniae are closely related organisms that are generally considered to be less-virulent opportunistic pathogens. We used a large, comprehensive, population-based strain collection and whole-genome sequencing to investigate infections caused by these organisms in our hospital system. We discovered that K. variicola and K. quasipneumoniae isolates are often misidentified as K. pneumoniae by routine clinical microbiology diagnostics and frequently cause severe life-threatening infections similar to K. pneumoniae . The presence of KPC in K. variicola and K. quasipneumoniae strains as well as NDM-1 metallo-beta-lactamase in one K. variicola strain is particularly concerning because these genes confer resistance to many different beta-lactam antibiotics. The sharing of plasmids, as well as evidence of homologous recombination, between these three species of Klebsiella is cause for additional concern. Klebsiella pneumoniae is a major threat to public health, causing significant morbidity and mortality worldwide. The emergence of highly drug-resistant strains is particularly concerning. There has been a recognition and division of Klebsiella pneumoniae into three distinct phylogenetic groups: Klebsiella pneumoniae , Klebsiella variicola , and Klebsiella quasipneumoniae . K. variicola and K. quasipneumoniae have often been described as opportunistic pathogens that have less virulence in humans than K. pneumoniae does. We recently sequenced the genomes of 1,777 extended-spectrum-beta-lactamase (ESBL)-producing K. pneumoniae isolates recovered from human infections and discovered that 28 strains were phylogenetically related to K . variicola and K. quasipneumoniae . Whole-genome sequencing of 95 additional non-ESBL-producing K. pneumoniae isolates recovered from patients found 12 K. quasipneumoniae strains. Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) analysis initially identified all patient isolates as K. pneumoniae , suggesting a potential pitfall in conventional clinical microbiology laboratory identification methods. Whole-genome sequence analysis revealed extensive sharing of core gene content and plasmid replicons among the Klebsiella species. For the first time, strains of both K. variicola and K. quasipneumoniae were found to carry the Klebsiella pneumoniae carbapenemase (KPC) gene, while another K. variicola strain was found to carry the New Delhi metallo-beta-lactamase 1 (NDM-1) gene. K. variicola and K. quasipneumoniae infections were not less virulent than K. pneumoniae infections, as assessed by in-hospital mortality and infection type. We also discovered evidence of homologous recombination in one K. variicola strain, as well as one strain from a novel Klebsiella species, which challenge the current understanding of interrelationships between clades of Klebsiella . IMPORTANCE Klebsiella pneumoniae is a serious human pathogen associated with resistance to multiple antibiotics and high mortality. K. variicola and K. quasipneumoniae are closely related organisms that are generally considered to be less-virulent opportunistic pathogens. We used a large, comprehensive, population-based strain collection and whole-genome sequencing to investigate infections caused by these organisms in our hospital system. We discovered that K. variicola and K. quasipneumoniae isolates are often misidentified as K. pneumoniae by routine clinical microbiology diagnostics and frequently cause severe life-threatening infections similar to K. pneumoniae . The presence of KPC in K. variicola and K. quasipneumoniae strains as well as NDM-1 metallo-beta-lactamase in one K. variicola strain is particularly concerning because these genes confer resistance to many different beta-lactam antibiotics. The sharing of plasmids, as well as evidence of homologous recombination, between these three species of Klebsiella is cause for additional concern.

We sequenced the genomes of 3,615 strains of serotype Emm protein 1 (M1) group A Streptococcus to unravel the nature and timing of molecular events contributing to the emergence, dissemination, and genetic diversification of an unusually virulent clone that now causes epidemic human infections worldwide. We discovered that the contemporary epidemic clone emerged in stepwise fashion from a precursor cell that first contained the phage encoding an extracellular DNase virulence factor (streptococcal DNase D2, SdaD2) and subsequently acquired the phage encoding the SpeA1 variant of the streptococcal pyrogenic exotoxin A superantigen. The SpeA2 toxin variant evolved from SpeA1 by a single-nucleotide change in the M1 progenitor strain before acquisition by horizontal gene transfer of a large chromosomal region encoding secreted toxins NAD ⁺-glycohydrolase and streptolysin O. Acquisition of this 36-kb region in the early 1980s into just one cell containing the phage-encoded sdaD2 and speA2 genes was the final major molecular event preceding the emergence and rapid intercontinental spread of the contemporary epidemic clone. Thus, we resolve a decades-old controversy about the type and sequence of genomic alterations that produced this explosive epidemic. Analysis of comprehensive, population-based contemporary invasive strains from seven countries identified strong patterns of temporal population structure. Compared with a preepidemic reference strain, the contemporary clone is significantly more virulent in nonhuman primate models of pharyngitis and necrotizing fasciitis. A key finding is that the molecular evolutionary events transpiring in just one bacterial cell ultimately have produced millions of human infections worldwide.

Over the last four years, each successive wave of the COVID-19 pandemic has been caused by variants with mutations that improve the transmissibility of the virus. Despite this, we still lack tools for predicting clinically important features of the virus. In this study, we show that it is possible to predict the PCR cycle threshold (Ct) values from clinical detection assays using sequence data. Ct values often correspond with patient viral load and the epidemiological trajectory of the pandemic. Using a collection of 36,335 high quality genomes, we built models from SARS-CoV-2 intrahost single nucleotide variant (iSNV) data, computing XGBoost models from the frequencies of A, T, G, C, insertions, and deletions at each position relative to the Wuhan-Hu-1 reference genome. Our best model had an R 2 of 0.604 [0.593–0.616, 95% confidence interval] and a Root Mean Square Error (RMSE) of 5.247 [5.156–5.337], demonstrating modest predictive power. Overall, we show that the results are stable relative to an external holdout set of genomes selected from SRA and are robust to patient status and the detection instruments that were used. This study highlights the importance of developing modeling strategies that can be applied to publicly available genome sequence data for use in disease prevention and control.

Klebsiella pneumoniae is a major human pathogen responsible for high morbidity and mortality rates. The emergence and spread of strains resistant to multiple antimicrobial agents and documented large nosocomial outbreaks are especially concerning. To develop new therapeutic strategies for K. pneumoniae , it is imperative to understand the population genomic structure of strains causing human infections. To address this knowledge gap, we sequenced the genomes of 1,777 extended-spectrum beta-lactamase-producing K. pneumoniae strains cultured from patients in the 2,000-bed Houston Methodist Hospital system between September 2011 and May 2015, representing a comprehensive, population-based strain sample. Strains of largely uncharacterized clonal group 307 (CG307) caused more infections than those of well-studied epidemic CG258. Strains varied markedly in gene content and had an extensive array of small and very large plasmids, often containing antimicrobial resistance genes. Some patients with multiple strains cultured over time were infected with genetically distinct clones. We identified 15 strains expressing the New Delhi metallo-beta-lactamase 1 (NDM-1) enzyme that confers broad resistance to nearly all beta-lactam antibiotics. Transcriptome sequencing analysis of 10 phylogenetically diverse strains showed that the global transcriptome of each strain was unique and highly variable. Experimental mouse infection provided new information about immunological parameters of host-pathogen interaction. We exploited the large data set to develop whole-genome sequence-based classifiers that accurately predict clinical antimicrobial resistance for 12 of the 16 antibiotics tested. We conclude that analysis of large, comprehensive, population-based strain samples can assist understanding of the molecular diversity of these organisms and contribute to enhanced translational research. IMPORTANCE Klebsiella pneumoniae causes human infections that are increasingly difficult to treat because many strains are resistant to multiple antibiotics. Clonal group 258 (CG258) organisms have caused outbreaks in health care settings worldwide. Using a comprehensive population-based sample of extended-spectrum beta-lactamase (ESBL)-producing K. pneumoniae strains, we show that a relatively uncommon clonal type, CG307, caused the plurality of ESBL-producing K. pneumoniae infections in our patients. We discovered that CG307 strains have been abundant in Houston for many years. As assessed by experimental mouse infection, CG307 strains were as virulent as pandemic CG258 strains. Our results may portend the emergence of an especially successful clonal group of antibiotic-resistant K. pneumoniae . Klebsiella pneumoniae causes human infections that are increasingly difficult to treat because many strains are resistant to multiple antibiotics. Clonal group 258 (CG258) organisms have caused outbreaks in health care settings worldwide. Using a comprehensive population-based sample of extended-spectrum beta-lactamase (ESBL)-producing K. pneumoniae strains, we show that a relatively uncommon clonal type, CG307, caused the plurality of ESBL-producing K. pneumoniae infections in our patients. We discovered that CG307 strains have been abundant in Houston for many years. As assessed by experimental mouse infection, CG307 strains were as virulent as pandemic CG258 strains. Our results may portend the emergence of an especially successful clonal group of antibiotic-resistant K. pneumoniae .

There is concern about second and subsequent waves of COVID-19 caused by the SARS-CoV-2 coronavirus occurring in communities globally that had an initial disease wave. Metropolitan Houston, TX, with a population of 7 million, is experiencing a massive second disease wave that began in late May 2020. To understand SARS-CoV-2 molecular population genomic architecture and evolution and the relationship between virus genotypes and patient features, we sequenced the genomes of 5,085 SARS-CoV-2 strains from these two waves. Our report provides the first molecular characterization of SARS-CoV-2 strains causing two distinct COVID-19 disease waves. We sequenced the genomes of 5,085 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains causing two coronavirus disease 2019 (COVID-19) disease waves in metropolitan Houston, TX, an ethnically diverse region with 7 million residents. The genomes were from viruses recovered in the earliest recognized phase of the pandemic in Houston and from viruses recovered in an ongoing massive second wave of infections. The virus was originally introduced into Houston many times independently. Virtually all strains in the second wave have a Gly614 amino acid replacement in the spike protein, a polymorphism that has been linked to increased transmission and infectivity. Patients infected with the Gly614 variant strains had significantly higher virus loads in the nasopharynx on initial diagnosis. We found little evidence of a significant relationship between virus genotype and altered virulence, stressing the linkage between disease severity, underlying medical conditions, and host genetics. Some regions of the spike protein—the primary target of global vaccine efforts—are replete with amino acid replacements, perhaps indicating the action of selection. We exploited the genomic data to generate defined single amino acid replacements in the receptor binding domain of spike protein that, importantly, produced decreased recognition by the neutralizing monoclonal antibody CR3022. Our report represents the first analysis of the molecular architecture of SARS-CoV-2 in two infection waves in a major metropolitan region. The findings will help us to understand the origin, composition, and trajectory of future infection waves and the potential effect of the host immune response and therapeutic maneuvers on SARS-CoV-2 evolution. IMPORTANCE There is concern about second and subsequent waves of COVID-19 caused by the SARS-CoV-2 coronavirus occurring in communities globally that had an initial disease wave. Metropolitan Houston, TX, with a population of 7 million, is experiencing a massive second disease wave that began in late May 2020. To understand SARS-CoV-2 molecular population genomic architecture and evolution and the relationship between virus genotypes and patient features, we sequenced the genomes of 5,085 SARS-CoV-2 strains from these two waves. Our report provides the first molecular characterization of SARS-CoV-2 strains causing two distinct COVID-19 disease waves.

Nosocomial transmission of pathogens is a major health care challenge. The increasing spread of antibiotic-resistant strains represents an ongoing threat to public health. Previous Staphylococcus aureus transmission studies have focused on transmission of S. aureus between asymptomatic carriers or used low-resolution typing methods such as multilocus sequence typing (MLST) or spa typing. To identify patient-to-patient intrahospital transmission using high-resolution genetic analysis, we sequenced the genomes of a consecutive set of 398 S. aureus isolates from sterile-site infections. The S. aureus strains were collected from four hospitals in the Houston Methodist Hospital System over a 6-month period. Importantly, we discovered no evidence of transmission of S. aureus between patients with sterile-site infections. The lack of intrahospital transmission may reflect a fundamental difference between day-to-day transmission events in the hospital setting and the more frequently studied outbreak scenarios. IMPORTANCE Previous studies have suggested that nosocomial transmission of S. aureus is common. Our data revealed an unexpected lack of evidence for intrahospital transmission of S. aureus between patients with invasive infections. This finding has important implications for hospital infection control and public health efforts. In addition, our data demonstrate that highly related pools of S. aureus strains exist in the community which may complicate outbreak investigations. Previous studies have suggested that nosocomial transmission of S. aureus is common. Our data revealed an unexpected lack of evidence for intrahospital transmission of S. aureus between patients with invasive infections. This finding has important implications for hospital infection control and public health efforts. In addition, our data demonstrate that highly related pools of S. aureus strains exist in the community which may complicate outbreak investigations.

This study integrated genomic sequencing, mouse virulence assays, and bacterial transcriptomic analysis to advance our understanding of the molecular mechanisms contributing to Streptococcus dysgalactiae subsp. equisimilis emm type stG62647 pathogenesis. We tested a large cohort of genetically closely related stG62647 isolates for virulence using an established mouse model of necrotizing myositis and discovered a broad spectrum of virulence phenotypes, with near-mortality rates ranging from 20% to 95%. This variation was unexpected, given their close genetic proximity. Transcriptome analysis of stG62647 isolates responsible for the lowest and highest near-mortality rates suggested that these isolates used multiple molecular pathways to alter their virulence. In addition, some genes encoding transcriptional regulators and putative virulence factors likely contribute to SDSE emm type stG62647 pathogenesis. These data underscore the complexity of pathogen–host interactions in an emerging SDSE clonal group.

Streptococcus dysgalactiae subspecies equisimilis (SDSE) has emerged as an increasingly important bacterial pathogen causing serious invasive infections in humans worldwide. Despite its clinical importance, the mechanisms through which SDSE causes infections remain poorly understood, and no licensed vaccine currently exists. SDSE can cause necrotizing myositis, an infection with high morbidity and mortality. We used a primate infection model and bacterial transcriptome analysis to gain new understanding of the molecular events contributing to SDSE pathogenesis in necrotizing myositis. Our results provide extensive new information about the transcriptome of SDSE in vivo and reveal numerous potential targets for future therapeutic and vaccine research.

Routine cervical cancer screening has significantly decreased the incidence and mortality of cervical cancer. As selection of proper screening modalities depends on well-validated clinical decision algorithms, retrospective review correlating cytology and HPV test results with cervical biopsy diagnosis is essential for validating and revising these algorithms to changing technologies, demographics, and optimal clinical practices. However, manual categorization of the free-text biopsy diagnosis into discrete categories is extremely laborious due to the overwhelming number of specimens, which may lead to significant error and bias. Advances in machine learning and natural language processing (NLP), particularly over the last decade, have led to significant accomplishments and impressive performance in computer-based classification tasks. In this work, we apply an efficient version of an NLP framework, FastText™, to an annotated cervical biopsy dataset to create a supervised classifier that can assign accurate biopsy categories to free-text biopsy interpretations with high concordance to manually annotated data (>99.6%). We present cases where the machine-learning classifier disagrees with previous annotations and examine these discrepant cases after referee review by an expert pathologist. We also show that the classifier is robust on an untrained external dataset, achieving a concordance of 97.7%. In conclusion, we demonstrate a useful application of NLP to a real-world pathology classification task and highlight the benefits and limitations of this approach.