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Brown, A.

Publications and source records attributed to Brown, A..

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Single-cell in situ transcriptomic map of astrocyte cortical layer diversity

During organogenesis, patterns and gradients of gene expression underlie organization and diversified cell specification to generate complex tissue architecture. While the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells are diversified to mimic neuronal laminae or show distinct layering. To determine the molecular architecture of the mammalian cortex, we developed a high content pipeline that can quantify single-cell gene expression in situ. The Large-area Spatial Transcriptomic (LaST) map confirmed expected cortical neuron layer organization and also revealed a novel neuronal identity signature. Screening 46 candidate genes for astrocyte diversity across the cortex, we identified grey matter superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from neurons. Astrocyte layers formed in early postnatal cortex and mostly persisted in adult mouse and human cortex. Mutations that shifted neuronal post-mitotic identity or organization were sufficient to alter glial layering, indicating an instructive role for neuronal cues. In normal mouse cortex, astrocyte layer patterns showed area diversity between functionally distinct cortical regions. These findings indicate that excitatory neurons and astrocytes cells are organized into distinct lineage-associated laminae, which give rise to higher order neuroglial complexity of cortical architecture.

neuroscience

A comprehensive genomics solution for HIV surveillance and clinical monitoring in a global health setting

High-throughput viral genetic sequencing is needed to monitor the spread of drug resistance, direct optimal antiretroviral regimes, and to identify transmission dynamics in generalised HIV epidemics. Public health efforts to sequence HIV genomes at scale face three major technical challenges: (i) minimising assay cost and protocol complexity, (ii) maximising sensitivity, and (iii) recovering accurate and unbiased sequences of both the genome consensus and the within-host viral diversity. Here we present a novel, high-throughput, virus-enriched sequencing method and computational pipeline tailored specifically to HIV (veSEQ-HIV), which addresses all three technical challenges, and can be used directly on leftover blood drawn for routine CD4 testing. We demonstrate its performance on 1,620 plasma samples collected from consenting individuals attending 10 large urban clinics in Zambia, partners of HPTN 071 (PopART). We show that veSEQ-HIV consistently recovers complete HIV genomes from the majority of samples of different subtypes, and is also quantitative: the number of HIV reads per sample obtained by veSEQ-HIV estimates viral load without the need for additional testing. Both quantitativity and sensitivity were assessed on a subset of 126 samples with clinically measured viral loads, and with standardized quantification controls (VL 100 - 5,000,000 RNA copies/ml). Complete HIV genomes were recovered from 93% (85/91) of samples when viral load was over 1,000 copies per ml. The quantitative nature of the assay implies that variant frequencies estimated with veSEQ-HIV are representative of true variant frequencies in the sample. Detection of minority variants can be exploited for epidemiological analysis of transmission and drug resistance, and we show how the information contained in individual reads of a veSEQ-HIV sample can be used to detect linkage between multiple mutations associated with resistance to antiretroviral therapy. Less than 2% of reads obtained by veSEQ-HIV were identified as in silico contamination events using updates to the phyloscanner software (phyloscanner clean) that we show to be 95% sensitive and 99% specific at decontaminating NGS data. The cost of the assay -- approximately 45 USD per sample -- compares favourably with existing VL and HIV genotyping tests, and provides the additional value of viral load quantification and inference of drug resistance with a single test. veSEQ-HIV is well suited to large public health efforts and is being applied to all [~]9000 samples collected for the HPTN 071-2 (PopART Phylogenetics) study.

genomics

Applying Inter-rater Reliability to Improve Consistency in Classifying PhD Career Outcomes

In the past year, there has been an exciting groundswell of national efforts to integrate multiple taxonomies for the transparent dissemination and analysis of PhD career outcomes. In this study, we leveraged the unique resources of the Broadening Experiences in Scientific Training Consortium to examine the reliability of the three-tiered Unified Career Outcomes Taxonomy (UCOT v.2017) that was collaboratively developed at a meeting convened by Rescuing Biomedical Research in August 2017. Using an amended version of the UCOT v.2017 (UCOT v.2017-rev1) and a new Supplementary Guidance document, we categorized over 570 PhD alumni records from three different universities. Utilizing Krippendorffs alpha to measure the interrater reliability from nine different individuals, we determined moderate to robust reproducibility within the first two tiers of the taxonomy (Workforce Sector and Career Type); however, the reliability for the third tier (Job Function) did not meet established standards. The team identified significant sources of error, revised category definitions, improved coder training materials and processes, and tested for improved reliability through coding 219 PhD alumni records using the revised taxonomy, UCOT v.2017-rev2. Our results revealed that the changes introduced in UCOT v.2017-rev2 improved inter-rater reliability in all three tiers, and either met or exceeded the acceptable standards for reliability. A final set of clarifications were made to UCOT v.2017-rev2, resulting in UCOT v.2018 and a Finalized Guidance document. Our findings underscore the importance of carefully developing guidance documents to aid coders in the reliable and consistent categorization of alumni career outcomes. We propose periodic assessment of the UCOT v.2018 to address the natural evolution of PhD careers in the global workforce. Ultimately, we hope that UCOT v.2018 will aid in the classification and dissemination of alumni career outcomes that is essential to educating trainees, institutions, and agencies about the diversity of career options for PhDs, and therein empower all PhDs to pursue the careers of their choice.

scientific communication and education

Methods matter: Influential purification and analysis parameters for intracellular parasite metabolomics

Metabolomics is increasingly popular for the study of many pathogens. For the malaria parasite, Plasmodium falciparum, both targeted and untargeted metabolite detection has improved our understanding of pathogenesis, host-parasite interactions, and antimalarial drug treatment and resistance. However, purification and analysis procedures for performing metabolomics on intracellular pathogens have not been explored. Here, we investigate the impact of host contamination on the metabolome when preparing samples using standard methods. We purified in vitro grown ring stage intra-erythrocytic P. falciparum parasites for untargeted metabolomics studies; the small size of this developmental stage amplifies the challenges associated with metabolomics studies as the ratio between host and parasite biomass is maximized. Following metabolite identification and data preprocessing, we investigated whether host contributions could be corrected post hoc using various normalization approaches (including double stranded DNA, total protein, or parasite number). We conclude that normalization parameters have large effects on differential abundance analysis and recommend the thoughtful selection of these parameters. However, normalization does not remove the contribution from the parasites extracellular environment (culture media and host erythrocyte). In fact, we found that extra-parasite material is as influential on the metabolome as treatment with a potent antimalarial drug with known metabolic effects (artemisinin). Because of this influence, we could not detect significant changes associated with drug treatment. Instead, we identified metabolites predictive of host and media contamination that can be used to assess sample purification. Our findings provide a basis for development of improved experimental and analytical methods for future metabolomics studies of intracellular organisms.

microbiology