Motivation -To curate and organize expensive spaceflight experiments conducted aboard space stations and maximize the scientific return of investment, while democratizing access to vast amounts of spaceflight related omics data generated from several model organisms. Results -The GeneLab Data System (GLDS) is an open access database containing fully coordinated and curated "omics" (genomics, transcriptomics, proteomics, metabolomics) data, detailed metadata and radiation dosimetry for a variety of model organisms. GLDS is supported by an integrated data system allowing federated search across several public bioinformatics repositories. Archived datasets can be queried using full-text search (e.g., keywords, Boolean and wildcards) and results can be sorted in multifactorial manner using assistive filters. GLDS also provides a collaborative platform built on GenomeSpace for sharing files and analyses with collaborators. It currently houses 172 datasets and supports standard guidelines for submission of datasets, MIAME (for microarray), ENCODE Consortium Guidelines (for RNA-seq) and MIAPE Guidelines (for proteomics).

The last five decades of molecular and systems biology research have provided unprecedented insights into the molecular and genetic basis of many cellular processes. Despite these insights, however, it is arguable that there is still only limited predictive understanding of cell behaviours. In particular, the basis of heterogeneity in single-cell behaviour and the initiation of many different metabolic, transcriptional or mechanical responses to environmental stimuli remain largely unexplained. To go beyond the status quo , the understanding of cell behaviours emerging from molecular genetics must be complemented with physical and physiological ones, focusing on the intracellular and extracellular conditions within and around cells. Here, we argue that such a combination of genetics, physics and physiology can be grounded on a bioelectrical conceptualization of cells. We motivate the reasoning behind such a proposal and describe examples where a bioelectrical view has been shown to, or can, provide predictive biological understanding. In addition, we discuss how this view opens up novel ways to control cell behaviours by electrical and electrochemical means, setting the stage for the emergence of bioelectrical engineering.

It is now established that the gut microbiome influences human neurology and behavior, and vice versa. Distinct mechanisms underlying this bidirectional communication pathway, termed the gut-brain axis, are becoming increasingly uncovered. This review summarizes recent interkingdom signaling research focused on gammaaminobutyric acid (GABA), a human neurotransmitter and ubiquitous signaling molecule found in bacteria, fungi, plants, invertebrates, and mammals. We detail how GABAergic signaling has been shown to be a crucial component of the gut-brain axis. We further describe how GABA is also being found to mediate interkingdom signaling between algae and invertebrates, plants and invertebrates, and plants and bacteria. Based on these emerging results, we argue that obtaining a complete understanding of GABA-mediated communication in the gut-brain axis will involve deciphering the role of GABA signaling and metabolism within bacterial communities themselves.

Abstract. Object-Relational database management system is an integrated hybrid cooperative approach to combine the best practices of both the relational model utilizing SQL queries and the object-oriented, semantic paradigm for supporting complex data creation. In this paper, a highly scalable, information on demand database framework, called NETMARK, is introduced. NETMARK takes advantages of the Oracle 8i object-relational database using physical addresses data types for very efficient keyword search of records spanning across both context and content. NETMARK was originally developed in early 2000 as a research and development prototype to solve the vast amounts of unstructured and semi-structured documents existing within NASA enterprises. Today, NETMARK is a flexible, high-throughput open database framework for managing, storing, and searching unstructured or semi-structured arbitrary hierarchal models, such as XML and HTML.

The field of synthetic biology seeks to program living cells to perform novel functions with applications ranging from environmental biosensing to smart cell‐based therapeutics. Bacteria are an especially attractive chassis organism due to their rapid growth, ease of genetic manipulation, and ability to persist across many environmental niches. Despite significant progress in bacterial synthetic biology, programming bacteria to perform novel functions outside the well‐controlled laboratory context remains challenging. In contrast to planktonic laboratory growth, bacteria in nature predominately reside in the context of densely packed communities known as biofilms. While biofilms have historically been considered environmental and biomedical hazards, their physiology and emergent behaviors could be leveraged for synthetic biology to engineer more capable and robust bacteria. Specifically, bacteria within biofilms participate in complex emergent behaviors such as collective organization, cell‐to‐cell signaling, and division of labor. Understanding and utilizing these properties can enable the effective deployment of engineered bacteria into natural target environments. Toward this goal, this review summarizes the current state of synthetic biology in biofilms by highlighting new molecular tools and remaining biological challenges. Looking to future opportunities, advancing synthetic biology in biofilms will enable the next generation of smart cell‐based technologies for use in medicine, biomanufacturing, and environmental remediation.