AMAnD: an automated metagenome anomaly detection methodology utilizing DeepSVDD neural networks.

The composition of metagenomic communities within the human body often reflects localized medical conditions such as upper respiratory diseases and gastrointestinal diseases. Fast and accurate computational tools to flag anomalous metagenomic samples from typical samples are desirable to understand different phenotypes, especially in contexts where repeated, long-duration temporal sampling is done. Here, we present Automated Metagenome Anomaly Detection (AMAnD), which utilizes two types of Deep Support Vector Data Description (DeepSVDD) models; one trained on taxonomic feature space output by the Pan-Genomics for Infectious Agents (PanGIA) taxonomy classifier and one trained on kmer frequency counts. AMAnD's semi-supervised one-class approach makes no assumptions about what an anomaly may look like, allowing the flagging of potentially novel anomaly types. Three diverse datasets are profiled. The first dataset is hosted on the National Center for Biotechnology Information's (NCBI) Sequence Read Archive (SRA) and contains nasopharyngeal swabs from healthy and COVID-19-positive patients. The second dataset is also hosted on SRA and contains gut microbiome samples from normal controls and from patients with slow transit constipation (STC). AMAnD can learn a typical healthy nasopharyngeal or gut microbiome profile and reliably flag the anomalous COVID+ or STC samples in both feature spaces. The final dataset is a synthetic metagenome created by the Critical Assessment of Metagenome Annotation Simulator (CAMISIM). A control dataset of 50 well-characterized organisms was submitted to CAMISIM to generate 100 synthetic control class samples. The experimental conditions included 12 different spiked-in contaminants that are taxonomically similar to organisms present in the laboratory blank sample ranging from one strain tree branch taxonomic distance away to one family tree branch taxonomic distance away. This experiment was repeated in triplicate at three different coverage levels to probe the dependence on sample coverage. AMAnD was again able to flag the contaminant inserts as anomalous. AMAnD's assumption-free flagging of metagenomic anomalies, the real-time model training update potential of the deep learning approach, and the strong performance even with lightweight models of low sample cardinality would make AMAnD well-suited to a wide array of applied metagenomics biosurveillance use-cases, from environmental to clinical utility.

Development and Optimization of an Unbiased, Metagenomics-Based Pathogen Detection Workflow for Infectious Disease and Biosurveillance Applications.

Rapid, specific, and sensitive identification of microbial pathogens is critical to infectious disease diagnosis and surveillance. Classical culture-based methods can be applied to a broad range of pathogens but have long turnaround times. Molecular methods, such as PCR, are time-effective but are not comprehensive and may not detect novel strains. Metagenomic shotgun next-generation sequencing (NGS) promises specific identification and characterization of any pathogen (viruses, bacteria, fungi, and protozoa) in a less biased way. Despite its great potential, NGS has yet to be widely adopted by clinical microbiology laboratories due in part to the absence of standardized workflows. Here, we describe a sample-to-answer workflow called PanGIA (Pan-Genomics for Infectious Agents) that includes simplified, standardized wet-lab procedures and data analysis with an easy-to-use bioinformatics tool. PanGIA is an end-to-end, multi-use workflow that can be used for pathogen detection and related applications, such as biosurveillance and biothreat detection. We performed a comprehensive survey and assessment of current, commercially available wet-lab technologies and open-source bioinformatics tools for each workflow component. The workflow includes total nucleic acid extraction from clinical human whole blood and environmental microbial forensic swabs as sample inputs, host nucleic acid depletion, dual DNA and RNA library preparation, shotgun sequencing on an Illumina MiSeq, and sequencing data analysis. The PanGIA workflow can be completed within 24 h and is currently compatible with bacteria and viruses. Here, we present data from the development and application of the clinical and environmental workflows, enabling the specific detection of pathogens associated with bloodstream infections and environmental biosurveillance, without the need for targeted assay development.

Amplicon Sequencing Minimal Information (ASqMI): Quality and Reporting Guidelines for Actionable Calls in Biodefense Applications.

BACKGROUND: Accurate, high-confidence data is critical for assessing potential biothreat incidents. In a biothreat event, false-negative and -positive results have serious consequences. Worst case scenarios can result in unnecessary shutdowns or fatalities at an exorbitant monetary and psychological cost, respectively. Quantitative PCR assays for agents of interest have been successfully used for routine biosurveillance. Recently, there has been increased impetus for adoption of amplicon sequencing (AS) for biosurveillance because it enables discrimination of true positives from near-neighbor false positives, as well as broad, simultaneous detection of many targets in many pathogens in a high-throughput scheme. However, the high sensitivity of AS can lead to false positives. Appropriate controls and workflow reporting can help address these challenges. OBJECTIVES: Data reporting standards are critical to data trustworthiness. The standards presented herein aim to provide a framework for method quality assessment in biodetection. METHODS: We present a set of standards, Amplicon Sequencing Minimal Information (ASqMI), developed under the auspices of the AOAC INTERNATIONAL Stakeholder Program on Agent Detection Assays for making actionable calls in biosurveillance applications. In addition to the first minimum information guidelines for AS, we provide a controls checklist and scoring scheme to assure AS run quality and assess potential sample contamination. RESULTS: Adoption of the ASqMI guidelines will improve data quality, help track workflow performance, and ultimately provide decision makers confidence to trust the results of this new and powerful technology. CONCLUSION: AS workflows can provide robust, confident calls for biodetection; however, due diligence in reporting and controls are needed. The ASqMI guideline is the first AS minimum reporting guidance document that also provides the means for end users to evaluate their workflows to improve confidence. HIGHLIGHTS: Standardized reporting guidance for actionable calls is critical to ensuring trustworthy data.

Molecular Detection of Biological Agents in the Field: Then and Now.

Molecular detection of biological agents in the field has traditionally relied on the use of quantitative real-time PCR (qPCR), which now includes commercially available instruments that can be used in the laboratory or field. Adapting this technology for field-forward applications necessitated innovation to minimize size, weight, and power requirements. Rugged, portable instruments, efficient power sources, freeze-dried reagents, data communications, and standard operating procedures for minimally trained users are some examples of limitations that have been overcome to allow qPCR-based data to be generated at the point of need. Despite the high specificity and sensitivity of qPCR, the assays require a priori sequence-based knowledge of the etiological agent to design and produce specific targeted assays with primers and probes. However, in many cases the etiological agent may not be known and pathogen identification must rely on the use of an untargeted screening method. By extracting, preparing, and sequencing all of the genomic material in a particular sample at once, known as metagenomics, a less biased view of the biological entities in that sample can be ascertained. Using metagenomics methods in the field requires the development and optimization of straightforward sample preparation, sequencing, and bioinformatics workflows reminiscent of the challenges faced during the development of field-forward qPCR 15 years ago. To review the state of qPCR and sequencing in the field, we summarized a panel discussion from the 2019 ASM Biothreats Conference. Our discussion focused on the development, evolution, and comparison of molecular methods for biological agents and their utility in the field.

Stroke knowledge among urban and frontier first responders and emergency medical technicians in Montana.

PURPOSE: To assess stroke knowledge and practice among frontier and urban emergency medical services (EMS) providers and to evaluate the need for additional prehospital stroke training opportunities in Montana. METHODS: In 2006, a telephone survey of a representative sample of EMS providers was conducted in Montana. Respondents were stratified into 2 groups: those working in urban and frontier counties. FINDINGS: Compared to EMS providers from urban counties, those from frontier counties were significantly more likely to be older (mean age 44.7 vs 40.1 years), have fewer personnel working in their service (mean 17.7 vs 28.6), to be located farther away from a computed tomography scan (CT scan) (mean 41.3 vs 17.6 miles), and to be volunteers (84% vs 49%). They were also less likely to have a stroke protocol (58% vs 66%) and use a stroke screening tool (36% vs 47%) than their urban counterparts. There were no significant differences between frontier and urban EMS respondents' ability to correctly identify 4 or more stroke warning signs (58% vs 61%), 4 or more stroke risk factors (46% vs 43%), or the 3-hour recombinant tissue plasminogen activator (rt-PA) treatment window (56% vs 57%). Approximately two thirds of respondents from urban and frontier counties believed they had adequate stroke knowledge, but 90% indicated they were interested in additional stroke-related training. CONCLUSIONS: Although stroke knowledge did not differ between urban and frontier groups, stroke screens and stroke protocols were less likely to be used in the frontier areas. Training opportunities and the implementation of stroke protocols and screening tools are needed for EMS providers, particularly in frontier counties.

Unbiased Strain-Typing of Arbovirus Directly from Mosquitoes Using Nanopore Sequencing: A Field-forward Biosurveillance Protocol.

The future of infectious disease surveillance and outbreak response is trending towards smaller hand-held solutions for point-of-need pathogen detection. Here, samples of Culex cedecei mosquitoes collected in Southern Florida, USA were tested for Venezuelan Equine Encephalitis Virus (VEEV), a previously-weaponized arthropod-borne RNA-virus capable of causing acute and fatal encephalitis in animal and human hosts. A single 20-mosquito pool tested positive for VEEV by quantitative reverse transcription polymerase chain reaction (RT-qPCR) on the Biomeme two3. The virus-positive sample was subjected to unbiased metatranscriptome sequencing on the Oxford Nanopore MinION and shown to contain Everglades Virus (EVEV), an alphavirus in the VEEV serocomplex. Our results demonstrate, for the first time, the use of unbiased sequence-based detection and subtyping of a high-consequence biothreat pathogen directly from an environmental sample using field-forward protocols. The development and validation of methods designed for field-based diagnostic metagenomics and pathogen discovery, such as those suitable for use in mobile "pocket laboratories", will address a growing demand for public health teams to carry out their mission where it is most urgent: at the point-of-need.

Availability of diagnostic and treatment services for acute stroke in frontier counties in Montana and Northern Wyoming.

CONTEXT: Rapid diagnosis and treatment of ischemic stroke can lead to improved patient outcomes. Hospitals in rural and frontier counties, however, face unique challenges in providing diagnostic and treatment services for acute stroke. PURPOSE: The aim of this study was to assess the availability of key diagnostic technology and programs for acute stroke evaluation and treatment in Montana and northern Wyoming. METHODS: In 2004, hospital medical directors or their designees were mailed a survey about the availability of diagnostic technology, programs, and personnel for acute stroke care. FINDINGS: Fifty-eight of 67 (87%) hospitals responded to the survey. Seventy-nine percent (46/58) of responding hospitals were located in frontier counties, with an average bed size of 18 (11 SD). Of the hospitals in frontier counties, 44% reported emergency medical services prehospital stroke identification programs, 39% had 24-hour computed tomography capability, 44% had an emergency department stroke protocol, and 61% had a recombinant tissue plasminogen activator protocol. Thirty percent of hospitals in frontier counties reported that they met 6-10 of the criteria established by the Brain Attack Coalition to improve acute stroke care compared to 67% of hospitals in the nonfrontier counties. CONCLUSION: A stroke network model could enhance care and improve outcomes for stroke victims in frontier counties.

Deep Subsurface Life from North Pond: Enrichment, Isolation, Characterization and Genomes of Heterotrophic Bacteria.

Studies of subsurface microorganisms have yielded few environmentally relevant isolates for laboratory studies. In order to address this lack of cultivated microorganisms, we initiated several enrichments on sediment and underlying basalt samples from North Pond, a sediment basin ringed by basalt outcrops underlying an oligotrophic water-column west of the Mid-Atlantic Ridge at 22°N. In contrast to anoxic enrichments, growth was observed in aerobic, heterotrophic enrichments from sediment of IODP Hole U1382B at 4 and 68 m below seafloor (mbsf). These sediment depths, respectively, correspond to the fringes of oxygen penetration from overlying seawater in the top of the sediment column and upward migration of oxygen from oxic seawater from the basalt aquifer below the sediment. Here we report the enrichment, isolation, initial characterization and genomes of three isolated aerobic heterotrophs from North Pond sediments; an Arthrobacter species from 4 mbsf, and Paracoccus and Pseudomonas species from 68 mbsf. These cultivated bacteria are represented in the amplicon 16S rRNA gene libraries created from whole sediments, albeit at low (up to 2%) relative abundance. We provide genomic evidence from our isolates demonstrating that the Arthrobacter and Pseudomonas isolates have the potential to respire nitrate and oxygen, though dissimilatory nitrate reduction could not be confirmed in laboratory cultures. The cultures from this study represent members of abundant phyla, as determined by amplicon sequencing of environmental DNA extracts, and allow for further studies into geochemical factors impacting life in the deep subsurface.

Rural community knowledge of stroke warning signs and risk factors.

INTRODUCTION: Rapid identification and treatment of ischemic stroke can lead to improved patient outcomes. Public education campaigns in selected communities have helped to increase knowledge about stroke, but most data represent large metropolitan centers working with academic institutions. Much less is known about knowledge of stroke among residents in rural communities. METHODS: In 2004, 800 adults aged 45 years and older from two Montana counties participated in a telephone survey using unaided questions to assess awareness of stroke warning signs and risk factors. The survey also asked respondents if they had a history of atrial fibrillation, diabetes, high blood pressure, high cholesterol, smoking, heart disease, or stroke. RESULTS: More than 70% of survey participants were able to correctly report two or more warning signs for stroke: numbness on any side of the face/body (45%) and speech difficulties (38%) were reported most frequently. More than 45% were able to correctly report two or more stroke risk factors: smoking (50%) and high blood pressure (44%) were reported most frequently. Respondents aged 45 to 64 years (odds ratio [OR] 2.44; 95% confidence interval [CI], 1.78-3.46), women (OR 2.02; 95% CI, 1.46-2.80), those with 12 or more years of education (OR 1.96; 95% CI, 1.08-3.56), and those with high cholesterol (OR 1.68; 95% CI, 1.17-2.42) were more likely to correctly identify two or more warning signs compared with respondents without these characteristics. Women (OR 1.48; 95% CI, 1.07-2.05) and respondents aged 45 to 64 years (OR 1.35; 95% CI, 1.01-1.81) were also more likely to correctly identify two or more stroke risk factors compared with men and older respondents. CONCLUSION: Residents of two rural counties were generally aware of stroke warning signs, but their knowledge of stroke risk factors was limited.

Perceived risk for developing stroke among older adults.

BACKGROUND: Persons who perceive their risk for stroke accurately may be more likely to engage in prevention practices to reduce their risk. METHODS: In 2004, 800 adults aged 45 years and older in two counties participated in a telephone survey to assess their perceived risk for stroke and their history of stroke risk factors. RESULTS: Overall, 39% of respondents perceived themselves to be at risk for having a stroke. In the multivariate analyses, younger age, current smoking, and a history of diabetes, high blood pressure, high cholesterol, heart disease, and stroke/TIA were independently associated with perceived risk for stroke. Respondents with atrial fibrillation were no more likely to report being at risk for stroke compared to respondents without atrial fibrillation. Perceived risk for stroke increased as the number of risk factors increased. However, 46% of respondents with three or more risk factors did not perceive themselves to be at risk. CONCLUSIONS: Many adults with multiple risk factors do not perceive themselves to be at risk for stroke. Clinical and public health efforts are needed to increase awareness of the risk for stroke.