Jolene R. Bowers

Background TB treatment is prescribed to millions of individuals yearly, and after cure these individuals often develop recurrent post-TB complications. There is little information exists at the intersection of TB and AMR (i.e., resistance in microbes other than M. tuberculosis complex).The ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp.) are considered key taxa in AMR acquisition. K. pneumoniae is a common isolate from blood stream infections in our setting, South Africa. Methods We used the Next-Gen Antimicrobial Resistance Detection (N-GARD) assay, a novel, multiplex, sequencing technique to profile AMR associated strains and genes present in stool of drug-susceptible and drug-resistant TB cases longitudinally. Results In both cohorts, no significant changes were seen in the proportion of ESKAPE or AMR associated strains during treatment, but trends were noted. The drug-susceptible cohort showed trends of longitudinal increases in AMR-related strains; Enterobacter cloacae, Klebsiella pnemoniae, Klebsiella varicola. Significant longitudinal decreases in AMR-related gyrA (Escherichia coli), fluctuations in tetD, strB and trends of increased FosA, qnrD, qnrA, Sul3 and SaM2 were seen in the drug susceptible cohort. The drug-resistant cohort showed significant increase in npmA and trends of longitudinal increases of ermA and sul1. We also noticed trends of single nucleotide polymorphisms. Conclusion Overall, the drug-resistant cohort had more significant changes in AMR-associated genes compared to drug susceptible cohort. These changes in the resistome during TB treatment require future investigation and future studies will involve more targeted analysis of identified trends. Funding: This project is part of the EDCTP2 programme supported by the European Union (grant number TMA2019CDF-2738-ESKAPE-TB) and is partly funded by the National Research Foundation.

In South Africa, Cryptococcus neoformans is the most common cause of adult meningitis. We performed multi locus sequence typing and fluconazole susceptibility testing of clinical C. neoformans isolates collected from 251 South African patients with cryptococcosis through national surveillance from 2005 to 2009. We examined the association between clinical characteristics of patients and genotype, and the effect of genotype on in-hospital mortality. We performed whole genome phylogenetic analysis of fifteen C. neoformans isolates with the molecular type VNB and tested their virulence in a Galleria mellonella model. Most isolates had the molecular type VNI (206/251, 82%), followed by VNII (25/251, 10%), VNB (15/251, 6%), and VNIV (5/251, 2%); 67 sequence types were identified. There were no differences in fluconazole minimum inhibitory concentration (MIC) values among molecular types and the majority of strains had low MIC values (MIC₅₀ of 1 µg/mL and MIC₉₀ of 4 µg/mL). Males were almost twice as likely of being infected with a non-VNI genotype (adjusted odds ratio [OR]: 1.65, 95% confidence interval [CI]: 0.25–10.99; p = 0.61). Compared to patients infected with a VNI genotype, those with a non-VNI genotype had a 50% reduced adjusted odds of dying in hospital (95% CI: 0.03–7.57; p = 0.62). However, for both these analyses, our estimates had wide confidence intervals spanning 1 with large p-values. Fifteen VNB strains were not as virulent in a G. mellonella larval model as the H99 reference strain. A majority of these VNB strains belonged to the VNBII clade and were very closely related by phylogenetic analysis.

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.

In December of 2019, a novel coronavirus, SARS-CoV-2, emerged in the city of Wuhan, China causing severe morbidity and mortality. Since then, the virus has swept across the globe causing millions of confirmed infections and hundreds of thousands of deaths. To better understand the nature of the pandemic and the introduction and spread of the virus in Arizona, we sequenced viral genomes from clinical samples tested at the TGen North Clinical Laboratory, provided to us by the Arizona Department of Health Services, and at Arizona State University and the University of Arizona, collected as part of community surveillance projects. Phylogenetic analysis of 79 genomes we generated from across Arizona revealed a minimum of 9 distinct introductions throughout February and March. We show that >80% of our sequences descend from clades that were initially circulating widely in Europe but have since dominated the outbreak in the United States. In addition, we show that the first reported case of community transmission in Arizona descended from the Washington state outbreak that was discovered in late February. Notably, none of the observed transmission clusters are epidemiologically linked to the original travel-related cases in the state, suggesting successful early isolation and quarantine. Finally, we use molecular clock analyses to demonstrate a lack of identifiable, widespread cryptic transmission in Arizona prior to the middle of February 2020.

Rhizopus spp. fungi are ubiquitous in the environment and a rare but substantial cause of infection in immunosuppressed persons and surgery patients. During 2005–2017, an abnormally high number of Rhizopus infections in surgery patients, with no apparent epidemiologic links, were reported in Argentina. To determine the likelihood of a common source of the cluster, we performed whole-genome sequencing on samples collected during 2006–2014. Most isolates were separated by >60 single-nucleotide polymorphisms, and we found no evidence for recombination or nonneutral mutation accumulation; these findings do not support common source or patient-to-patient transmission. Assembled genomes of most isolates were ≈25 Mbp, and multiple isolates had substantially larger assembled genomes (43–51 Mbp), indicative of infections with strain types that underwent genome expansion. Whole-genome sequencing has become an essential tool for studying epidemiology of fungal infections. Less discriminatory techniques may miss true relationships, possibly resulting in inappropriate attribution of point source.

Altered intestinal microbiota is associated with systemic and intestinal diseases, such as inflammatory bowel disease (IBD). Dysbiotic microbiota with enhanced proinflammatory capacity is characterized by depletion of anaerobic commensals, increased proportion of facultatively anaerobic bacteria, as well as reduced diversity and stability. In this study, we developed a high-throughput in vitro screening assay to isolate intestinal commensal bacteria with anti-inflammatory capacity from a healthy fecal microbiota transplantation donor. Freshly isolated gut bacteria were screened for their capacity to attenuate Escherichia coli lipopolysaccharide (LPS)-induced interleukin 8 (IL-8) release from HT-29 cells. The screen yielded a number of Bacteroides and Parabacteroides isolates, which were identified as P. distasonis, B. caccae, B. intestinalis, B. uniformis, B. fragilis, B. vulgatus and B. ovatus using whole genome sequencing. We observed that a cell-cell contact with the epithelium was not necessary to alleviate in vitro inflammation as spent culture media from the isolates were also effective and the anti-inflammatory action did not correlate with the enterocyte adherence capacity of the isolates. The anti-inflammatory isolates also exerted enterocyte monolayer reinforcing action and lacked essential genes to synthetize hexa-acylated, proinflammatory lipid A, part of LPS. Yet, the anti-inflammatory effector molecules remain to be identified. The Bacteroides strains isolated and characterized in this study have potential to be used as so-called next-generation probiotics.

Antimicrobial resistance (AMR) in the nosocomial pathogen, Acinetobacter baumannii , is becoming a serious public health threat. While some mechanisms of AMR have been reported, understanding novel mechanisms of resistance is critical for identifying emerging resistance. One of the first steps in identifying novel AMR mechanisms is performing genotype/phenotype association studies. However, performing genotype/phenotype association studies is complicated by the plastic nature of the A. baumannii pan-genome. In this study, we compared the antibiograms of 12 antimicrobials associated with multiple drug families for 84 A. baumannii isolates, many isolated in Arizona, USA. in silico screening of these genomes for known AMR mechanisms failed to identify clear correlations for most drugs. We then performed a genome wide association study (GWAS) looking for associations between all possible 21-mers; this approach generally failed to identify mechanisms that explained the resistance phenotype. In order to decrease the genomic noise associated with population stratification, we compared four phylogenetically-related pairs of isolates with differing susceptibility profiles. RNA-Sequencing (RNA-Seq) was performed on paired isolates and differentially expressed genes were identified. In these isolate pairs, we identified four different potential mechanisms, highlighting the difficulty of broad AMR surveillance in this species. To verify and validate differential expression, amplicon sequencing was performed. These results suggest that a diagnostic platform based on gene expression rather than genomics alone may be beneficial in certain surveillance efforts. The implementation of such advanced diagnostics coupled with increased AMR surveillance will potentially improve A. baumannii infection treatment and patient outcomes.

Enteroviruses frequently result in respiratory and gastrointestinal illness; however, multiple subtypes, including poliovirus, can cause severe neurologic disease. Recent biennial increases (i.e., 2014, 2016, and 2018) in cases of non-polio acute flaccid paralysis have led to speculations that other enteroviruses, specifically enterovirus D68 (EV-D68), are emerging to fill the niche that was left from poliovirus eradication. A cluster of 11 suspect cases of pediatric acute flaccid myelitis (AFM) was identified in 2016 in Phoenix, AZ. Multiple genomic analyses identified the presence of EV-D68 in the majority of clinical AFM cases. Beyond limited detection of herpesvirus, no other likely etiologies were found in the cluster. These findings strengthen the likelihood that EV-D68 is a cause of AFM and show that the rapid molecular assays developed for this study are useful for investigations of AFM and EV-D68.