TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization.

Introduction: The clinical incidence of antimicrobial-resistant fungal infections has dramatically increased in recent years. Certain fungal pathogens colonize various body cavities, leading to life-threatening bloodstream infections. However, the identification and characterization of fungal isolates in laboratories remain a significant diagnostic challenge in medicine and public health. Whole-genome sequencing provides an unbiased and uniform identification pipeline for fungal pathogens but most bioinformatic analysis pipelines focus on prokaryotic species. To this end, TheiaEuk_Illumina_PE_PHB (TheiaEuk) was designed to focus on genomic analysis specialized to fungal pathogens. Methods: TheiaEuk was designed using containerized components and written in the workflow description language (WDL) to facilitate deployment on the cloud-based open bioinformatics platform Terra. This species-agnostic workflow enables the analysis of fungal genomes without requiring coding, thereby reducing the entry barrier for laboratory scientists. To demonstrate the usefulness of this pipeline, an ongoing outbreak of C. auris in southern Nevada was investigated. We performed whole-genome sequence analysis of 752 new C. auris isolates from this outbreak. Furthermore, TheiaEuk was utilized to observe the accumulation of mutations in the FKS1 gene over the course of the outbreak, highlighting the utility of TheiaEuk as a monitor of emerging public health threats when combined with whole-genome sequencing surveillance of fungal pathogens. Results: A primary result of this work is a curated fungal database containing 5,667 unique genomes representing 245 species. TheiaEuk also incorporates taxon-specific submodules for specific species, including clade-typing for Candida auris (C. auris). In addition, for several fungal species, it performs dynamic reference genome selection and variant calling, reporting mutations found in genes currently associated with antifungal resistance (FKS1, ERG11, FUR1). Using genome assemblies from the ATCC Mycology collection, the taxonomic identification module used by TheiaEuk correctly assigned genomes to the species level in 126/135 (93.3%) instances and to the genus level in 131/135 (97%) of instances, and provided zero false calls. Application of TheiaEuk to actual specimens obtained in the course of work at a local public health laboratory resulted in 13/15 (86.7%) correct calls at the species level, with 2/15 called at the genus level. It made zero incorrect calls. TheiaEuk accurately assessed clade type of Candida auris in 297/302 (98.3%) of instances. Discussion: TheiaEuk demonstrated effectiveness in identifying fungal species from whole genome sequence. It further showed accuracy in both clade-typing of C. auris and in the identification of mutations known to associate with drug resistance in that organism.

The use of whole-genome sequencing and development of bioinformatics to monitor overlapping outbreaks of Candida auris in southern Nevada.

A Candida auris outbreak has been ongoing in Southern Nevada since August 2021. In this manuscript we describe the sequencing of over 200 C. auris isolates from patients at several facilities. Genetically distinct subgroups of C. auris were detected from Clade I (3 distinct lineages) and III (1 lineage). Open-source bioinformatic tools were developed and implemented to aid in the epidemiological investigation. The work herein compares three methods for C. auris whole genome analysis: Nullarbor, MycoSNP and a new pipeline TheiaEuk. We also describe a novel analysis method focused on elucidating phylogenetic linkages between isolates within an ongoing outbreak. Moreover, this study places the ongoing outbreaks in a global context utilizing existing sequences provided worldwide. Lastly, we describe how the generated results were communicated to the epidemiologists and infection control to generate public health interventions.

Analysis of SARS-CoV-2 variants from patient specimens in Nevada from October 2020 to August 2021.

In early 2020, the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the human population quickly developed into a global pandemic. SARS-CoV-2 is the etiological agent of coronavirus disease 2019 (COVID-19) which has a broad range of respiratory illnesses. As the virus circulates, it acquires nucleotide changes. These mutations are potentially due to the inherent differences in the selection pressures within the human population compared to the original zoonotic reservoir of SARS-CoV-2 and formerly naïve humans. The acquired mutations will most likely be neutral, but some may have implications for viral transmission, disease severity, and resistance to therapies or vaccines. This is a follow-up study from our early report (Hartley et al. J Genet Genomics. 01202021;48(1):40-51) which detected a rare variant (nsp12, RdRp P323F) circulating within Nevada in mid 2020 at high frequency. The primary goals of the current study were to determine the phylogenetic relationship of the SARS-CoV-2 genomes within Nevada and to determine if there are any unusual variants within Nevada compared to the current database of SARS-CoV-2 sequences. Whole genome sequencing and analysis of SARS-CoV-2 from 425 positively identified nasopharyngeal/nasal swab specimens were performed from October 2020 to August 2021 to determine any variants that could result in potential escape from current therapeutics. Our analysis focused on nucleotide mutations that generated amino acid variations in the viral Spike (S) protein, Receptor binding domain (RBD), and the RNA-dependent RNA-polymerase (RdRp) complex. The data indicate that SARS-CoV-2 sequences from Nevada did not contain any unusual variants that had not been previously reported. Additionally, we did not detect the previously identified the RdRp P323F variant in any of the samples. This suggests that the rare variant we detected before was only able to circulate because of the stay-at-home orders and semi-isolation experience during the early months of the pandemic. IMPORTANCE: SARS-COV-2 continues to circulate in the human population. In this study, SARS-CoV-2 positive nasopharyngeal/nasal swab samples were used for whole genome sequencing to determine the phylogenetic relationship of SARS-CoV-2 sequences within Nevada from October 2020 to August 2021. The resulting data is being added to a continually growing database of SARS-CoV-2 sequences that will be important for understanding the transmission and evolution of the virus as it spreads around the globe.

Rapid Lineage Assignment of Severe Acute Respiratory Syndrome Coronavirus 2 Cases through Automated Library Preparation, Sequencing, and Bioinformatic Analysis.

The coronavirus disease 2019 (COVID-19) pandemic has provided a stage to illustrate that there is considerable value in obtaining rapid, whole-genome-based information about pathogens. This article describes the utility of a commercially available, automated severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) library preparation, genome sequencing, and a bioinformatics analysis pipeline to provide rapid, near-real-time SARS-CoV-2 variant description. This study evaluated the turnaround time, accuracy, and other quality-related parameters obtained from commercially available automated sequencing instrumentation, from analysis of continuous clinical samples obtained from January 1, 2021, to October 6, 2021. This analysis included a base-by-base assessment of sequencing accuracy at every position in the SARS-CoV-2 chromosome using two commercially available methods. Mean turnaround time, from the receipt of a specimen for SARS-CoV-2 testing to the availability of the results, with lineage assignment, was <3 days. Accuracy of sequencing by one method was 100%, although certain sites on the genome were found repeatedly to have been sequenced with varying degrees of read error rate.

Use of wastewater surveillance for early detection of Alpha and Epsilon SARS-CoV-2 variants of concern and estimation of overall COVID-19 infection burden.

A decline in diagnostic testing for SARS-CoV-2 is expected to delay the tracking of COVID-19 variants of concern and interest in the United States. We hypothesize that wastewater surveillance programs provide an effective alternative for detecting emerging variants and assessing COVID-19 incidence, particularly when clinical surveillance is limited. Here, we analyzed SARS-CoV-2 RNA in wastewater from eight locations across Southern Nevada between March 2020 and April 2021. Trends in SARS-CoV-2 RNA concentrations (ranging from 4.3 log10 gc/L to 8.7 log10 gc/L) matched trends in confirmed COVID-19 incidence, but wastewater surveillance also highlighted several limitations with the clinical data. Amplicon-based whole genome sequencing (WGS) of 86 wastewater samples identified the B.1.1.7 (Alpha) and B.1.429 (Epsilon) lineages in December 2020, but clinical sequencing failed to identify the variants until January 2021, thereby demonstrating that 'pooled' wastewater samples can sometimes expedite variant detection. Also, by calibrating fecal shedding (11.4 log10 gc/infection) and wastewater surveillance data to reported seroprevalence, we estimate that ~38% of individuals in Southern Nevada had been infected by SARS-CoV-2 as of April 2021, which is significantly higher than the 10% of individuals confirmed through clinical testing. Sewershed-specific ascertainment ratios (i.e., X-fold infection undercounts) ranged from 1.0 to 7.7, potentially due to demographic differences. Our data underscore the growing application of wastewater surveillance in not only the identification and quantification of infectious agents, but also the detection of variants of concern that may be missed when diagnostic testing is limited or unavailable.

Characterization of Anopheles stephensi Odorant Receptor 8, an Abundant Component of the Mouthpart Chemosensory Transcriptome.

Several mosquito species within the genus Anopheles are vectors for human malaria, and the spread of this disease is driven by the propensity of certain species to feed preferentially on humans. The study of olfaction in mosquitoes is important to understand dynamics of host-seeking and host-selection; however, the majority of these studies focus on Anopheles gambiae or An. coluzzii, both vectors of malaria in Sub-Saharan Africa. Other malaria vectors may recognize different chemical cues from potential hosts; therefore, in this study, we investigated An. stephensi, the south Asian malaria mosquito. We specifically focused on the mouthparts (primarily the maxillary palp and labella) that have been much less investigated compared to the antennae but are also important for host-seeking. To provide a broad view of chemoreceptor expression, RNAseq was used to examine the transcriptomes from the mouthparts of host-seeking females, blood-fed females, and males. Notably, AsOr8 had a high transcript abundance in all transcriptomes and was, therefore, cloned and expressed in the Drosophila empty neuron system. This permitted characterization with a panel of odorants that were selected, in part, for their presence in the human odor profile. The responsiveness of AsOr8 to odorants was highly similar to An. gambiae Or8 (AgOr8), except for sulcatone, which was detected by AsOr8 but not AgOr8. Subtle differences in the receptor sensitivity to specific odorants may provide clues to species- or strain-specific approaches to host-seeking and host selection. Further exploration of the profile of An. stephensi chemosensory proteins may yield a better understanding of how different malaria vectors navigate host-finding and host-choice.