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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.

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.

ABSTRACT 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.

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 site U1382B at 4 and 68 meters 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, and initial characterizations 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 environmentally significant phyla, and allow for further studies into geochemical factors impacting life in the deep subsurface.

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], 1.783.46), women (OR 2.02; 95% CI, 1.462.80), those with 12 or more years of education (OR 1.96; 95% CI, 1.083.56), and those with high cholesterol (OR 1.68; 95% CI, 1.172.42) were more likely to correctly identify two or more warning signs compared with respondents without these characteristics. Women (OR 1.48; 95% CI, 1.072.05) and respondents aged 45 to 64 years (OR 1.35; 95% CI, 1.011.81) 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.

Abstract Objective To collect real‐world data on the safety and effectiveness of balloon dilation of the Eustachian tube using a seeker‐based device in patients with persistent/chronic symptoms of Eustachian tube dysfunction. Methods A multicenter, prospective, single‐arm registry was conducted from June 2018 through August 2020 at 10 US centers, including tertiary care and private practices. Primary endpoints included mean change from baseline in the 7‐item Eustachian Tube Dysfunction Questionnaire (ETDQ‐7) and the serious related adverse event rate. Secondary endpoints include changes in middle ear assessments, surgical intervention rate, and changes in Sino‐Nasal Outcome Test and Work and Activity Impairment (WPAI) questionnaires. Results A total of 169 participants were treated with balloon dilation of the Eustachian tube, with 166 and 154 participants completing the 6‐week and 6‐month follow‐ups, respectively. Repeated measures analysis of the change in ETDQ‐7 scores indicated statistically significant improvement (−2.1; 95% CI −2.40, −1.84; P

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p

Chemotaxis enhances the fitness of Salmonella enterica serotype Typhimurium (S. Typhimurium) during colitis. However, the chemotaxis receptors conferring this fitness advantage and their cognate signals generated during inflammation remain unknown. Here we identify respiratory electron acceptors that are generated in the intestinal lumen as by-products of the host inflammatory response as in vivo signals for methyl-accepting chemotaxis proteins (MCPs). Three MCPs, including Trg, Tsr and Aer, enhanced the fitness of S. Typhimurium in a mouse colitis model. Aer mediated chemotaxis towards electron acceptors (energy taxis) in vitro and required tetrathionate respiration to confer a fitness advantage in vivo. Tsr mediated energy taxis towards nitrate but not towards tetrathionate in vitro and required nitrate respiration to confer a fitness advantage in vivo. These data suggest that the energy taxis receptors Tsr and Aer respond to distinct in vivo signals to confer a fitness advantage upon S. Typhimurium during inflammation by enabling this facultative anaerobic pathogen to seek out favorable spatial niches containing host-derived electron acceptors that boost its luminal growth.