Graphical abstract

Salmonella enterica is an important foodborne pathogen that uses secreted effector proteins to manipulate host pathways to facilitate survival and dissemination. Different S. enterica serovars cause disease syndromes ranging from gastroenteritis to typhoid fever and vary in their effector repertoire. We leveraged this natural diversity to identify stm2585, here designated sarA (Salmonella anti-inflammatory response activator), as a Salmonella effector that induces production of the anti-inflammatory cytokine IL-10. RNA-seq of cells infected with either ΔsarA or wild-type S. Typhimurium revealed that SarA activates STAT3 transcriptional targets. Consistent with this, SarA is necessary and sufficient for STAT3 phosphorylation, STAT3 inhibition blocks IL-10 production, and SarA and STAT3 interact by co-immunoprecipitation. These effects of SarA contribute to intracellular replication in vitro and bacterial load at systemic sites in mice. Our results demonstrate the power of using comparative genomics for identifying effectors and that Salmonella has evolved mechanisms for activating an important anti-inflammatory pathway.

No abstract

Open data that is free and publicly available without restrictions is critical for progress in any scientific discipline and has been the cornerstone of sound and reproducible genomics research. Microbiome research is still a relatively young, thriving, active research field, with great biomedical potential. As a large data-driven research field, microbiome projects can include hundreds or even thousands of participants, samples, and associated background ("metadata") parameters. Processing this data, identifying meaningful associations, and determining significance depends on complex, often non-standardized bioinformatics and biostatistics protocols. Reproducibility, transparency, and expandability of these protocols to review, evaluate, and build upon this work is crucial to fulfill on the promise of microbiome research and maintain credibility. At the absolute minimum, unrestricted access to the raw sequencing data and associated metadata is needed and has been recognized and implemented by the scientific community, some journals, and funding agencies. In practice, access to open protocols for data processing and analysis is also important to promote reproducibility and advances in the field but rarely provided. Unfortunately, there appears to be an increasing number of studies that are failing to satisfy even basic, community-accepted standards. Motivated by a number of recent negative experiences in our own research projects, as well as our interaction with authors aiming to publish in Microbiome, this editorial aims to shed light on common problems in the field and make recommendations to reinforce a culture of open data and protocols for microbiome research.