ProteoVision: web server for advanced visualization of ribosomal proteins.

ProteoVision is a web server designed to explore protein structure and evolution through simultaneous visualization of multiple sequence alignments, topology diagrams and 3D structures. Starting with a multiple sequence alignment, ProteoVision computes conservation scores and a variety of physicochemical properties and simultaneously maps and visualizes alignments and other data on multiple levels of representation. The web server calculates and displays frequencies of amino acids. ProteoVision is optimized for ribosomal proteins but is applicable to analysis of any protein. ProteoVision handles internally generated and user uploaded alignments and connects them with a selected structure, found in the PDB or uploaded by the user. It can generate de novo topology diagrams from three-dimensional structures. All displayed data is interactive and can be saved in various formats as publication quality images or external datasets or PyMol Scripts. ProteoVision enables detailed study of protein fragments defined by Evolutionary Classification of protein Domains (ECOD) classification. ProteoVision is available at http://proteovision.chemistry.gatech.edu/.

Genomic Analysis of the Predominant Strains and Antimicrobial Resistance Determinants Within 1479 Neisseria gonorrhoeae Isolates From the US Gonococcal Isolate Surveillance Project in 2018.

BACKGROUND: The prevalence of Neisseria gonorrhoeae (GC) isolates with elevated minimum inhibitory concentrations to various antibiotics continues to rise in the United States and globally. Genomic analysis provides a powerful tool for surveillance of circulating strains, antimicrobial resistance determinants, and understanding of transmission through a population. METHODS: Neisseria gonorrhoeae isolates collected from the US Gonococcal Isolate Surveillance Project in 2018 (n = 1479) were sequenced and characterized. Whole-genome sequencing was used to identify sequence types, antimicrobial resistance profiles, and phylogenetic relationships across demographic and geographic populations. RESULTS: Genetic characterization identified that (1) 80% of the GC isolates were represented in 33 multilocus sequence types, (2) isolates clustered in 23 major phylogenetic clusters with select phenotypic and demographic prevalence, and (3) common antimicrobial resistance determinants associated with low-level or high-level decreased susceptibility or resistance to relevant antibiotics. CONCLUSIONS: Characterization of this 2018 Gonococcal Isolate Surveillance Project genomic data set, which is the largest US whole-genome sequence data set to date, sets the basis for future prospective studies, and establishes a genomic baseline of GC populations for local and national monitoring.

Exploring and Comparing the Structure of Sexual Networks Affected by Neisseria gonorrhoeae Using Sexual Partner Services Investigation and Genomic Data.

BACKGROUND: Sexual networks are difficult to construct because of incomplete sexual partner data. The proximity of people within a network may be inferred from genetically similar infections. We explored genomic data combined with partner services investigation (PSI) data to extend our understanding of sexual networks affected by Neisseria gonorrhoeae (NG). METHODS: We used 2017-2019 PSI and whole-genome sequencing (WGS) data from 8 jurisdictions participating in Centers for Disease Control and Prevention's Strengthening the US Response to Resistant Gonorrhea (SURRG) project. Clusters were identified from sexual contacts and through genetically similar NG isolates. Sexual mixing patterns were characterized by describing the clusters by the individual's gender and gender of their sex partners. RESULTS: Our study included 4627 diagnoses of NG infection (81% sequenced), 2455 people received a PSI, 393 people were negative contacts of cases, and 495 were contacts with an unknown NG status. We identified 823 distinct clusters using PSI data combined with WGS data. Of cases that were not linked to any other case using PSI data, 37% were linked when using WGS data. Overall, 40% of PSI cases were allocated to a larger cluster when PSI and WGS data were combined compared with PSI data alone. Mixed clusters containing women, men who report sex with women, and men who report sex with men were common when using the WGS data either alone or in combination with the PSI data. CONCLUSIONS: Combining PSI and WGS data improves our understanding of sexual network connectivity.

Fluorescent sialic derivatives for the specific detection of influenza viruses.

Early and accurate diagnosis of influenza viruses can decrease its harmful impact. Here, we have synthesized fluorescent sialic acid derivatives that are cleaved by influenza neuraminidases (NAs) and not by Streptococcus pneumoniae that also inhabits the human olfactory. We have also attempted to develop assays that could differentiate between influenza virus and S. pneumoniae by taking advantage of the structural differences between NAs from these pathogens.

Detection of Enzymes, Viruses, and Bacteria Using Glucose Meters.

We have developed innovative assays that can detect enzymes rapidly. Paracetamol- or catechol-bearing compounds, when exposed to their respective enzymes, released paracetamol or catechol, which can be detected using a standard glucose meter. This approach was used to detect a number of diverse analytes that include enzymes such as ß-galactosidase and α-mannosidase and pathogens such as influenza viruses, Streptococcus pneumoniae, and E. coli rapidly. The limit of detection for all analytes was extremely low and clinically relevant for influenza viruses. We also demonstrate that glucose oxidase or glucose dehydrogenase is not required because the paracetamol gets oxidized directly on the electrode surface. This indicates that test strips without glucose oxidase or dehydrogenase can be used, and we can detect analytes in the presence of high levels of background glucose. We demonstrate this unique nature of the assay to detect paracetamol in simulated urine and sheep blood without background interference of intrinsic glucose, indicating that glucose meters can be used to detect nonglucose analytes without background glucose interference.

Genetic basis of clarithromycin resistance in Bacillus anthracis.

The high-consequence pathogen Bacillus anthracis causes human anthrax and often results in lethal infections without the rapid administration of effective antimicrobial treatment. Antimicrobial resistance profiling is therefore critical to inform post-exposure prophylaxis and treatment decisions, especially during emergencies such as outbreaks or where intentional release is suspected. Whole-genome sequencing using a rapid long-read sequencer can uncover antimicrobial resistance patterns if genetic markers of resistance are known. To identify genomic markers associated with antimicrobial resistance, we isolated B. anthracis derived from the avirulent Sterne strain with elevated minimal inhibitory concentrations to clarithromycin. Mutants were characterized both phenotypically through broth microdilution susceptibility testing and observations during culturing, as well as genotypically with whole-genome sequencing. We identified two different in-frame insertions in the L22 ribosomal protein-encoding gene rplV, which were subsequently confirmed to be involved in clarithromycin resistance through the reversion of the mutant gene to the parent (drug-susceptible) sequence. Detection of the rplV insertions was possible with rapid long-read sequencing, with a time-to-answer within 3 h. The mutations associated with clarithromycin resistance described here will be used in conjunction with known genetic markers of resistance for other antimicrobials to strengthen the prediction of antimicrobial resistance in B. anthracis.IMPORTANCEThe disease anthrax, caused by the pathogen Bacillus anthracis, is extremely deadly if not treated quickly and appropriately. Clarithromycin is an antibiotic recommended for the treatment and post-exposure prophylaxis of anthrax by the Centers for Disease Control and Prevention; however, little is known about the ability of B. anthracis to develop resistance to clarithromycin or the mechanism of that resistance. The characterization of clarithromycin-resistant isolates presented here provides valuable information for researchers and clinicians in the event of a release of the resistant strain. Additionally, knowledge of the genetic basis of resistance provides a foundation for susceptibility prediction through rapid genome sequencing to inform timely treatment decisions.

Genomic analysis of 1710 surveillance-based Neisseria gonorrhoeae isolates from the USA in 2019 identifies predominant strain types and chromosomal antimicrobial-resistance determinants.

This study characterized high-quality whole-genome sequences of a sentinel, surveillance-based collection of 1710 Neisseria gonorrhoeae (GC) isolates from 2019 collected in the USA as part of the Gonococcal Isolate Surveillance Project (GISP). It aims to provide a detailed report of strain diversity, phylogenetic relationships and resistance determinant profiles associated with reduced susceptibilities to antibiotics of concern. The 1710 isolates represented 164 multilocus sequence types and 21 predominant phylogenetic clades. Common genomic determinants defined most strains' phenotypic, reduced susceptibility to current and historic antibiotics (e.g. bla TEM plasmid for penicillin, tetM plasmid for tetracycline, gyrA for ciprofloxacin, 23S rRNA and/or mosaic mtr operon for azithromycin, and mosaic penA for cefixime and ceftriaxone). The most predominant phylogenetic clade accounted for 21 % of the isolates, included a majority of the isolates with low-level elevated MICs to azithromycin (2.0 µg ml-1), carried a mosaic mtr operon and variants in PorB, and showed expansion with respect to data previously reported from 2018. The second largest clade predominantly carried the GyrA S91F variant, was largely ciprofloxacin resistant (MIC ≥1.0 µg ml-1), and showed significant expansion with respect to 2018. Overall, a low proportion of isolates had medium- to high-level elevated MIC to azithromycin ((≥4.0 µg ml-1), based on C2611T or A2059G 23S rRNA variants). One isolate carried the penA 60.001 allele resulting in elevated MICs to cefixime and ceftriaxone of 1.0 µg ml-1. This high-resolution snapshot of genetic profiles of 1710 GC sequences, through a comparison with 2018 data (1479 GC sequences) within the sentinel system, highlights change in proportions and expansion of select GC strains and the associated genetic mechanisms of resistance. The knowledge gained through molecular surveillance may support rapid identification of outbreaks of concern. Continued monitoring may inform public health responses to limit the development and spread of antibiotic-resistant gonorrhoea.

Highly specific and rapid glycan based amperometric detection of influenza viruses.

Rapid and precise detection of influenza viruses in a point of care setting is critical for applying appropriate countermeasures. Current methods such as nucleic acid or antibody based techniques are expensive or suffer from low sensitivity, respectively. We have developed an assay that uses glucose test strips and a handheld potentiostat to detect the influenza virus with high specificity. Influenza surface glycoprotein neuraminidase (NA), but not bacterial NA, cleaved galactose bearing substrates, 4,7di-OMe N-acetylneuraminic acid attached to the 3 or 6 position of galactose, to release galactose. In contrast, viral and bacterial NA cleaved the natural substrate, N-acetylneuraminic acid attached to the 3 or 6 position of galactose. The released galactose was detected amperometrically using a handheld potentiostat and dehydrogenase bearing glucose test strips. The specificity for influenza was confirmed using influenza strains and different respiratory pathogens that include Streptococcus pneumoniae and Haemophilus influenzae; bacteria do not cleave these molecules. The assay was also used to detect co-infections caused by influenza and bacterial NA. Viral drug susceptibility and testing with human clinical samples was successful in 15 minutes, indicating that this assay could be used to rapidly detect influenza viruses at primary care or resource poor settings using ubiquitous glucose meters.

Validity of the indicator organism paradigm for pathogen reduction in reclaimed water and public health protection.

The validity of using indicator organisms (total and fecal coliforms, enterococci, Clostridium perfringens, and F-specific coliphages) to predict the presence or absence of pathogens (infectious enteric viruses, Cryptosporidium, and Giardia) was tested at six wastewater reclamation facilities. Multiple samplings conducted at each facility over a 1-year period. Larger sample volumes for indicators (0.2 to 0.4 liters) and pathogens (30 to 100 liters) resulted in more sensitive detection limits than are typical of routine monitoring. Microorganisms were detected in disinfected effluent samples at the following frequencies: total coliforms, 63%; fecal coliforms, 27%; enterococci, 27%; C. perfringens, 61%; F-specific coliphages, approximately 40%; and enteric viruses, 31%. Cryptosporidium oocysts and Giardia cysts were detected in 70% and 80%, respectively, of reclaimed water samples. Viable Cryptosporidium, based on cell culture infectivity assays, was detected in 20% of the reclaimed water samples. No strong correlation was found for any indicator-pathogen combination. When data for all indicators were tested using discriminant analysis, the presence/absence patterns for Giardia cysts, Cryptosporidium oocysts, infectious Cryptosporidium, and infectious enteric viruses were predicted for over 71% of disinfected effluents. The failure of measurements of single indicator organism to correlate with pathogens suggests that public health is not adequately protected by simple monitoring schemes based on detection of a single indicator, particularly at the detection limits routinely employed. Monitoring a suite of indicator organisms in reclaimed effluent is more likely to be predictive of the presence of certain pathogens, and a need for additional pathogen monitoring in reclaimed water in order to protect public health is suggested by this study.