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BackgroundGenomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling.ResultsOf total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1–44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2–95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance.ConclusionsUse of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation.

Development of antibody protection during SARS-CoV-2 infection is a pressing question for public health and for vaccine development. We developed highly sensitive SARS-CoV-2-specific antibody and neutralization assays. SARS-CoV-2 Spike protein or Nucleocapsid protein specific IgG antibodies at titers more than 1:100,000 were detectable in all PCR+ subjects (n = 115) and were absent in the negative controls. Other isotype antibodies (IgA, IgG1-4) were also detected. SARS-CoV-2 neutralization was determined in COVID-19 and convalescent plasma at up to 10,000-fold dilution, using Spike protein pseudotyped lentiviruses, which were also blocked by neutralizing antibodies (NAbs). Hospitalized patients had up to 3000-fold higher antibody and neutralization titers compared to outpatients or convalescent plasma donors. Interestingly, some COVID-19 patients also possessed NAbs against SARS-CoV Spike protein pseudovirus. Together these results demonstrate the high specificity and sensitivity of our assays, which may impact understanding the quality or duration of the antibody response during COVID-19 and in determining the effectiveness of potential vaccines., Using SARS-CoV-2-specific antibody- and neutralization assays, Dogan et al find that hospitalized individuals show higher IgG antibody responses and higher neutralization titers compared to outpatient or convalescent plasma donors, providing insights into the host humoral response to SARS CoV-2.

Development of antibody protection during SARS-CoV-2 (CoV-2) infection is a pressing question for public health and for vaccine development. We developed highly sensitive CoV-2-specific antibody and neutralization assays. CoV-2 Spike protein or Nucleocapsid protein specific IgG antibodies at titers more than 1:100,000 were detectable in all PCR+ subjects (n=87) and were absent in the negative controls. Other isotype antibodies (IgA, IgG1-4) were also detected. CoV-2 neutralization was determined in COVID-19 and convalescent plasma up to 10,000-fold dilution, using Spike protein pseudotyped lentiviruses, which was also blocked by neutralizing antibodies (NAbs). Hospitalized patients had up to 3000-fold higher antibody and neutralization titers compared to outpatients or convalescent plasma donors. Further, subjects who donated plasma further out from the diagnosis of COVID-19 appeared to have lower titers. Interestingly, some COVID-19 patients also contained NAbs against SARS Spike protein pseudovirus. Together these results demonstrate the high specificity and sensitivity of our assays, which may impact understanding the quality or duration of the antibody response during COVID-19 and in determining the effectiveness of potential vaccines.

In the United States, federal law and many state laws differentiate between marijuana and industrial hemp through delta-9-tetrahydrocannabinol (THC) levels, whereby the latter is defined as ≤0.3 percent THC on a dry weight basis. Many traditional cannabis identification methods employed by crime laboratories cannot accurately determine total THC quantities in accordance with federal and state regulations, or do so with increased time, labor, and risks of instrument damage. In order to quickly distinguish positive marijuana samples, a method was developed to identify plant material with a total THC level >1%. This novel, automated dispersive pipette extraction (DPX) method uses tip-based technology and an automated liquid handler to enable fast, hands-free selective isolation of THC and its precursors for downstream gas chromatography-mass spectrometry (GC-MS) analysis. The workflow proceeds with no repetitive manual effort and reduced need for instrument maintenance while enabling crime labs to legally identify marijuana through the detection of total THC above 1%. Recovery of THC using the DPX extraction method was 93% at 30 µg/mL and 78% at 500 µg/mL. Similarly, THCA-A recovery was 100% at 30 µg/mL and 74% at 500 µg/mL. Samples evaluated in a blind study (proficiency, hemp, and nonprobative case samples) were all accurately identified as greater than or less than 1% THC, with samples containing

Summary Metagenomic inferences of bacterial strain diversity and infectious disease transmission studies largely assume a dominant, within-individual haplotype. We hypothesize that within-individual bacterial population diversity is critical for homeostasis of a healthy microbiome and infection risk. We characterized the evolutionary trajectory and functional distribution of Staphylococcus epidermidis—a keystone skin microbe and opportunistic pathogen. Analyzing 1,482 S. epidermidis genomes from 5 healthy individuals, we found that skin S. epidermidis isolates coalesce into multiple founder lineages rather than a single colonizer. Transmission events, natural selection, and pervasive horizontal gene transfer result in population admixture within skin sites and dissemination of antibiotic resistance genes within-individual. We provide experimental evidence for how admixture can modulate virulence and metabolism. Leveraging data on the contextual microbiome, we assess how interspecies interactions can shape genetic diversity and mobile gene elements. Our study provides insights into how within-individual evolution of human skin microbes shapes their functional diversification.

Genetic testing for the breast and ovarian cancer susceptibility genes BRCA1 and BRCA2 has important implications for the clinical management of people found to carry a mutation. However, genetic testing is expensive and may be associated with adverse psychosocial effects. To provide a cost-efficient and clinically appropriate genetic counselling service, genetic testing should be targeted at those individuals most likely to carry pathogenic mutations. Several algorithms that predict the likelihood of carrying a BRCA1 or a BRCA2 mutation are currently used in clinical practice to identify such individuals.We evaluated the performance of the carrier prediction algorithms BOADICEA, BRCAPRO, IBIS, the Manchester scoring system and Myriad tables, using 1934 families seen in cancer genetics clinics in the UK in whom an index patient had been screened for BRCA1 and/or BRCA2 mutations. The models were evaluated for calibration, discrimination and accuracy of the predictions.Of the five algorithms, only BOADICEA predicted the overall observed number of mutations detected accurately (ie, was well calibrated). BOADICEA also provided the best discrimination, being significantly better (p0.05) than all models except BRCAPRO (area under the receiver operating characteristic curve statistics: BOADICEA = 0.77, BRCAPRO = 0.76, IBIS = 0.74, Manchester = 0.75, Myriad = 0.72). All models underpredicted the number of BRCA1 and BRCA2 mutations in the low estimated risk category.Carrier prediction algorithms provide a rational basis for counselling individuals likely to carry BRCA1 or BRCA2 mutations. Their widespread use would improve equity of access and the cost-effectiveness of genetic testing.

The paper describes research into charging mechanisms for the delivery of digitized texts to students in the higher education sector. A satisfactory pricing model in this domain is urgently required. The history and background of the use and pricing of digitized texts for students in the higher education sector is examined. Issues of economics in the electronic era are described. The issues involved are outlined in relation to the stakeholders involved, namely academics, authors, the CLA (Copyright Licensing Agency), HERON (Higher Education Resources On-demand) libraries in the HE sector, publishers and students. Past projects and research conducted to date are considered and the results discussed. Particular reference is made to the HERON project, a service provided for the UK higher education community that delivers copyright clearance, digitization and delivery of the text to UK Higher Education Institutions (HEIs). HERON is also building up a national database and resource bank of the texts. Other electronic resource models are considered, in particular library initiatives. International projects are covered in relation to how pricing issues are addressed throughout the world, particularly in the USA. The case is proposed of the benefits to all stakeholders of establishing a mutually acceptable pricing model for the distribution of digitized texts to the HE/FE community. The PELICAN project had the ultimate aim of developing pricing models for the delivery of digitized text to the UK HE community, satisfying all stakeholders as far as possible. The project’s initial research findings are described, including a table of the possible pricing mechanisms and initial conclusions drawn.