OpenCell: Endogenous tagging for the cartography of human cellular organization

Elucidating the wiring diagram of the human cell is a central goal of the postgenomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery. We found that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions, and that RNA binding proteins form a specific subgroup defined by unique interaction and localization properties. Paired with a fully interactive website (opencell.czbiohub.org), our work constitutes a resource for the quantitative cartography of human cellular organization.

IDseq-An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring

BACKGROUND

Metagenomic next-generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource-limited environments.

FINDINGS

We present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline, which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics that are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2.

CONCLUSION

The IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.

Soil greenhouse gas emissions from Australian sports fields

Managed turf is a potential net source of greenhouse gas (GHG) emissions. While most studies to date have focused on non-sports turf, sports turf may pose an even greater risk of high GHG emissions due to the generally more intensive fertiliser, irrigation and mowing regimes. This study used manual and automated chambers to measure nitrous oxide (N₂O) and methane (CH₄) emissions from three sports fields and an area of non-sports turf in southern Australia. Over 213 days (autumn to late spring), the average daily N₂O emission was 37.6 g N ha^-1day^-1 at a sports field monitored at least weekly and cumulative N₂O emission was 2.5 times higher than the adjacent non-sports turf. Less frequent seasonal sampling at two other sports fields showed average N₂O daily emission ranging from 26 to 90 g N ha^-1 day^-1. Management practices associated with periods of relatively high N₂O emissions were surface renovation and herbicide application. CH₄ emissions at all of the sports fields were generally negligible with the exception of brief periods when soil was waterlogged following heavy rainfall where emissions of up to 1.3 kg C ha^-1 day^-1 were recorded. Controlled release and nitrification inhibitor containing fertilisers didn't reduce N₂O, CH₄ or CO₂ emissions relative to urea in a short term experiment. The N₂O emissions from the sports fields, and even the lower emissions from the non-sports turf, were relatively high compared to other land uses in Australia highlighting the importance of accounting for these emissions at a national level and investigating mitigation practices.

Cognitive and biochemical processes in depressed adult outpatients: a test of the circular process model

The circular process model is a psychobiological model of depression, in which it is postulated that catecholamines and negative cognitions interact to influence depression. Since its publication, there have been no empirical tests to support or refute the model. This study tested the model in 92 depressed adult outpatients with non-bipolar non-psychotic depression. There were no significant bivariate correlations among the biochemical and cognitive measures. However, the interactive model was supported by results of two out of three hierarchical regression analyses, in which the biochemical-by-cognitive interactive terms significantly predicted depression after the main effects of each variable were accounted for. These findings show sufficient evidence in support of the Circular Process Model to warrant further testing over the treatment period.