Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research.

Research increasingly relies on interrogating large-scale data resources. The NIH National Heart, Lung, and Blood Institute developed the NHLBI BioData CatalystⓇ (BDC), a community-driven ecosystem where researchers, including bench and clinical scientists, statisticians, and algorithm developers, find, access, share, store, and compute on large-scale datasets. This ecosystem provides secure, cloud-based workspaces, user authentication and authorization, search, tools and workflows, applications, and new innovative features to address community needs, including exploratory data analysis, genomic and imaging tools, tools for reproducibility, and improved interoperability with other NIH data science platforms. BDC offers straightforward access to large-scale datasets and computational resources that support precision medicine for heart, lung, blood, and sleep conditions, leveraging separately developed and managed platforms to maximize flexibility based on researcher needs, expertise, and backgrounds. Through the NHLBI BioData Catalyst Fellows Program, BDC facilitates scientific discoveries and technological advances. BDC also facilitated accelerated research on the coronavirus disease-2019 (COVID-19) pandemic.

Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space.

The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL; https://anvilproject.org) was developed to address a widespread community need for a unified computing environment for genomics data storage, management, and analysis. In this perspective, we present AnVIL, describe its ecosystem and interoperability with other platforms, and highlight how this platform and associated initiatives contribute to improved genomic data sharing efforts. The AnVIL is a federated cloud platform designed to manage and store genomics and related data, enable population-scale analysis, and facilitate collaboration through the sharing of data, code, and analysis results. By inverting the traditional model of data sharing, the AnVIL eliminates the need for data movement while also adding security measures for active threat detection and monitoring and provides scalable, shared computing resources for any researcher. We describe the core data management and analysis components of the AnVIL, which currently consists of Terra, Gen3, Galaxy, RStudio/Bioconductor, Dockstore, and Jupyter, and describe several flagship genomics datasets available within the AnVIL. We continue to extend and innovate the AnVIL ecosystem by implementing new capabilities, including mechanisms for interoperability and responsible data sharing, while streamlining access management. The AnVIL opens many new opportunities for analysis, collaboration, and data sharing that are needed to drive research and to make discoveries through the joint analysis of hundreds of thousands to millions of genomes along with associated clinical and molecular data types.

Microbial diversity in an intensively managed landscape is structured by landscape connectivity.

Intensively managed land increases the rate of nutrient and particle transport within a basin, but the impact of these changes on microbial community assembly patterns at the basin scale is not yet understood. The objective of this study was to investigate how landscape connectivity and dispersal impacts microbial diversity in an agricultural-dominated watershed. We characterized soil, sediment and water microbial communities along the Upper Sangamon River basin in Illinois-a 3600 km2 watershed strongly influenced by human activity, especially landscape modification and extensive fertilization for agriculture. We employed statistical and network analyses to reveal the microbial community structure and interactions in the critical zone (water, soil and sediment media). Using a Bayesian source tracking approach, we predicted microbial community connectivity within and between the environments. We identified strong connectivity within environments (up to 85.4 ± 13.3% of sequences in downstream water samples sourced from upstream samples, and 44.7 ± 26.6% in soil and sediment samples), but negligible connectivity across environments, which indicates that microbial dispersal was successful within but not between environments. Species sorting based on sample media type and environmental parameters was the dominant driver of community dissimilarity. Finally, we constructed operational taxonomic unit association networks for each environment and identified a number of co-occurrence relationships that were shared between habitats, suggesting that these are likely to be ecologically significant.

Pseudomonas aeruginosa facilitates Campylobacter jejuni growth in biofilms under oxic flow conditions.

We investigated the growth of Campylobacter jejuni in biofilms with Pseudomonas aeruginosa under oxic flow conditions. We observed the growth of C. jejuni in mono-culture, deposited on pre-established P. aeruginosa biofilms, and co-inoculated with P. aeruginosa. In mono-culture, C. jejuni was unable to form biofilms. However, deposited C. jejuni continuously grew on pre-established P. aeruginosa biofilms for a period of 3 days. The growth of scattered C. jejuni clusters was strictly limited to the P. aeruginosa biofilm surface, and no intergrowth was observed. Co-culturing of C. jejuni and P. aeruginosa also enabled the growth of both organisms in biofilms, with C. jejuni clusters developing on the surface of the P. aeruginosa biofilm. Dissolved oxygen (DO) measurements in the medium showed that P. aeruginosa biofilms depleted the effluent DO from 9.0 to 0.5 mg L(-1) 24 hours after inoculation. The localized microaerophilic environment generated by P. aeruginosa promoted the persistence and growth of C. jejuni. Our findings show that P. aeruginosa not only prolongs the survival of C. jejuni under oxic conditions, but also enables the growth of C. jejuni on the surface of P. aeruginosa biofilms.

Methods for characterizing the co-development of biofilm and habitat heterogeneity.

Biofilms are surface-attached microbial communities that have complex structures and produce significant spatial heterogeneities. Biofilm development is strongly regulated by the surrounding flow and nutritional environment. Biofilm growth also increases the heterogeneity of the local microenvironment by generating complex flow fields and solute transport patterns. To investigate the development of heterogeneity in biofilms and interactions between biofilms and their local micro-habitat, we grew mono-species biofilms of Pseudomonas aeruginosa and dual-species biofilms of P. aeruginosa and Escherichia coli under nutritional gradients in a microfluidic flow cell. We provide detailed protocols for creating nutrient gradients within the flow cell and for growing and visualizing biofilm development under these conditions. We also present protocols for a series of optical methods to quantify spatial patterns in biofilm structure, flow distributions over biofilms, and mass transport around and within biofilm colonies. These methods support comprehensive investigations of the co-development of biofilm and habitat heterogeneity.

Pseudomonas aeruginosa promotes Escherichia coli biofilm formation in nutrient-limited medium.

Biofilms have been implicated as an important reservoir for pathogens and commensal enteric bacteria such as Escherichia coli in natural and engineered water systems. However, the processes that regulate the survival of E. coli in aquatic biofilms have not been thoroughly studied. We examined the effects of hydrodynamic shear and nutrient concentrations on E. coli colonization of pre-established Pseudomonas aeruginosa biofilms, co-inoculation of E. coli and P. aeruginosa biofilms, and P. aeruginosa colonization of pre-established E. coli biofilms. In nutritionally-limited R2A medium, E. coli dominated biofilms when co-inoculated with P. aeruginosa, and successfully colonized and overgrew pre-established P. aeruginosa biofilms. In more enriched media, P. aeruginosa formed larger clusters, but E. coli still extensively overgrew and colonized the interior of P. aeruginosa clusters. In mono-culture, E. coli formed sparse and discontinuous biofilms. After P. aeruginosa was introduced to these biofilms, E. coli growth increased substantially, resulting in patterns of biofilm colonization similar to those observed under other sequences of organism introduction, i.e., E. coli overgrew P. aeruginosa and colonized the interior of P. aeruginosa clusters. These results demonstrate that E. coli not only persists in aquatic biofilms under depleted nutritional conditions, but interactions with P. aeruginosa can greatly increase E. coli growth in biofilms under these experimental conditions.

Temporal variations in the abundance and composition of biofilm communities colonizing drinking water distribution pipes.

Pipes that transport drinking water through municipal drinking water distribution systems (DWDS) are challenging habitats for microorganisms. Distribution networks are dark, oligotrophic and contain disinfectants; yet microbes frequently form biofilms attached to interior surfaces of DWDS pipes. Relatively little is known about the species composition and ecology of these biofilms due to challenges associated with sample acquisition from actual DWDS. We report the analysis of biofilms from five pipe samples collected from the same region of a DWDS in Florida, USA, over an 18 month period between February 2011 and August 2012. The bacterial abundance and composition of biofilm communities within the pipes were analyzed by heterotrophic plate counts and tag pyrosequencing of 16S rRNA genes, respectively. Bacterial numbers varied significantly based on sampling date and were positively correlated with water temperature and the concentration of nitrate. However, there was no significant relationship between the concentration of disinfectant in the drinking water (monochloramine) and the abundance of bacteria within the biofilms. Pyrosequencing analysis identified a total of 677 operational taxonomic units (OTUs) (3% distance) within the biofilms but indicated that community diversity was low and varied between sampling dates. Biofilms were dominated by a few taxa, specifically Methylomonas, Acinetobacter, Mycobacterium, and Xanthomonadaceae, and the dominant taxa within the biofilms varied dramatically between sampling times. The drinking water characteristics most strongly correlated with bacterial community composition were concentrations of nitrate, ammonium, total chlorine and monochloramine, as well as alkalinity and hardness. Biofilms from the sampling date with the highest nitrate concentration were the most abundant and diverse and were dominated by Acinetobacter.