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Bacterial metabolism plays a fundamental role in gut microbiota ecology and host-microbiome interactions. Yet the metabolic capabilities of most gut bacteria have remained unknown. Here we report growth characteristics of 96 phylogenetically diverse gut bacterial strains across 4 rich and 15 defined media. The vast majority of strains (76) grow in at least one defined medium, enabling accurate assessment of their biosynthetic capabilities. These do not necessarily match phylogenetic similarity, thus indicating a complex evolution of nutritional preferences. We identify mucin utilizers and species inhibited by amino acids and short-chain fatty acids. Our analysis also uncovers media for in vitro studies wherein growth capacity correlates well with in vivo abundance. Further value of the underlying resource is demonstrated by correcting pathway gaps in available genome-scale metabolic models of gut microorganisms. Together, the media resource and the extracted knowledge on growth abilities widen experimental and computational access to the gut microbiota.

A Western lifestyle with high salt consumption can lead to hypertension and cardiovascular disease. High salt may additionally drive autoimmunity by inducing T helper 17 (T H 17) cells, which can also contribute to hypertension. Induction of T H 17 cells depends on gut microbiota; however, the effect of salt on the gut microbiome is unknown. Here we show that high salt intake affects the gut microbiome in mice, particularly by depleting Lactobacillus murinus. Consequently, treatment of mice with L. murinus prevented salt-induced aggravation of actively induced experimental autoimmune encephalomyelitis and salt-sensitive hypertension by modulating T H 17 cells. In line with these findings, a moderate high-salt challenge in a pilot study in humans reduced intestinal survival of Lactobacillus spp., increased T H 17 cells and increased blood pressure. Our results connect high salt intake to the gut-immune axis and highlight the gut microbiome as a potential therapeutic target to counteract salt-sensitive conditions.

In the recent years, there is accumulating evidence for a strong impact of medication on the gut microbiota composition. This evidence comes from metagenomics-based associations and extends beyond classical antibacterials to a handful of human-targeted drugs. To answer whether such effects are direct and explore their consequences in human health, we need to develop experimental platforms that will allow for systematic profiling of drug-microbiota interactions. Here, we discuss approaches, considerations, experimental setups and strategies that can be used to tackle this need, but can be also readily transmitted to related questions in the microbiome field. A comprehensive understanding of how therapeutics interact with gut microbes will open up the path for further mechanistic dissection of such interactions, and ultimately improve not only our understanding of the gut microbiome, but also drug safety and efficacy., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Chemical-genetic approaches are based on measuring the cellular outcome of combining genetic and chemical perturbations in large-numbers in tandem. In these approaches the contribution of every gene to the fitness of an organism is measured upon exposure to different chemicals. Current technological advances enable the application of chemical genetics to almost any organism and at an unprecedented throughput. Here we review the underlying concepts behind chemical genetics, present its different vignettes and illustrate how such approaches can propel drug discovery., (© 2017 The Authors.)

Advances in our ability to systematically introduce and track controlled genetic variance in microorganisms have, in the past decade, fuelled high-throughput reverse genetics approaches. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing insights into the underlying pathways and the overall cellular network organization. Yet, until now, all efforts to quantify microbial macroscopic phenotypes have been restricted to monitoring growth in a small number of model microorganisms. We have developed an image analysis software named Iris, which allows for systematic exploration of a number of orthogonal-to-growth processes, including biofilm formation, colony morphogenesis, envelope biogenesis, sporulation and reporter activity. In addition, Iris provides more sensitive growth measurements than currently available software and is compatible with a variety of different microorganisms, as well as with endpoint or kinetic data. We used Iris to reanalyse existing chemical genomics data in Escherichia coli and to perform proof-of-principle screens on colony biofilm formation and morphogenesis of different bacterial species and the pathogenic fungus Candida albicans. We thereby recapitulated existing knowledge but also identified a plethora of additional genes and pathways involved in both processes.

Upon environmental changes, bacteria reschedule gene expression by directing alternative sigma factors to core RNA polymerase (RNAP). This sigma factor switch is achieved by regulating relative amounts of alternative sigmas and by decreasing the competitiveness of the dominant housekeeping sigma(70). Here we report that during stationary phase, the unorthodox Crl regulator supports a specific sigma factor, sigma(S) (RpoS), in its competition with sigma(70) for core RNAP by increasing the formation of sigma(S)-containing RNAP holoenzyme, Esigma(S). Consistently, Crl has a global regulatory effect in stationary phase gene expression exclusively through sigma(S), that is, on sigma(S)-dependent genes only. Not a specific promoter motif, but sigma(S) availability determines the ability of Crl to exert its function, rendering it of major importance at low sigma(S) levels. By promoting the formation of Esigma(S), Crl also affects partitioning of sigma(S) between RNAP core and the proteolytic sigma(S)-targeting factor RssB, thereby playing a dual role in fine-tuning sigma(S) proteolysis. In conclusion, Crl has a key role in reorganising the Escherichia coli transcriptional machinery and global gene expression during entry into stationary phase.

Different environmental stimuli cause bacteria to exchange the sigma subunit in the RNA polymerase (RNAP) and, thereby, tune their gene expression according to the newly emerging needs. Sigma factors are usually thought to recognize clearly distinguishable promoter DNA determinants, and thereby activate distinct gene sets, known as their regulons. In this review, we illustrate how the principle sigma factor in stationary phase and in stressful conditions in Escherichia coli, sigmaS (RpoS), can specifically target its large regulon in vivo, although it is known to recognize the same core promoter elements in vitro as the housekeeping sigma factor, sigma70 (RpoD). Variable combinations of cis-acting promoter features and trans-acting protein factors determine whether a promoter is recognized by RNAP containing sigmaS or sigma70, or by both holoenzymes. How these promoter features impose sigmaS selectivity is further discussed. Moreover, additional pathways allow sigmaS to compete more efficiently than sigma70 for limiting amounts of core RNAP (E) and thereby enhance EsigmaS formation and effectiveness. Finally, these topics are discussed in the context of sigma factor evolution and the benefits a cell gains from retaining competing and closely related sigma factors with overlapping sets of target genes.

The P2 promoter of proP, encoding a transporter for proline and glycine betaine in Escherichia coli, is a unique paradigm, where master regulators of different growth stages, Fis and sigma(S) (RpoS), collaborate to achieve promoter activation. It is also the only case described where Fis functions as class II transcriptional activator (centred at -41). Here we show that the degenerate -35 sequence, and the location of the Fis binding site, which forces a suboptimal 16 bp spacing between the -35 and -10 elements, allow only sigma(S) but not sigma(70) to function at proP (P2). Moreover, the interface between Fis and sigma(S) seems better suited to sigma(S), due to a single residue difference between sigma(S) and sigma(70). Nevertheless, Fis can activate RNA polymerase containing sigma(70) at a proP (P2) promoter variant, in which a typical sigma(70)-35 recognition sequence has been introduced at a 17 bp distance from the -10 hexamer. In summary, we elucidate the rules that govern sigma factor selectivity in the presence of a class II activator, provide new insight into transcriptional activation by Fis from this position, and clarify, why the proP (P2) promoter is precisely activated during a short time window of the growth cycle, when Fis and sigma(S) are both present.

The sigmaS (RpoS) subunit of RNA polymerase in Escherichia coli is a key master regulator which allows this bacterial model organism and important pathogen to adapt to and survive environmentally rough times. While hardly present in rapidly growing cells, sigmaS strongly accumulates in response to many different stress conditions, partly replaces the vegetative sigma subunit in RNA polymerase and thereby reprograms this enzyme to transcribe sigmaS-dependent genes (up to 10% of the E. coli genes). In this review, we summarize the extremely complex regulation of sigmaS itself and multiple signal input at the level of this master regulator, we describe the way in which sigmaS specifically recognizes "stress" promoters despite their similarity to vegetative promoters, and, while being far from comprehensive, we give a short overview of the far-reaching physiological impact of sigmaS. With sigmaS being a central and multiple signal integrator and master regulator of hundreds of genes organized in regulatory cascades and sub-networks or regulatory modules, this system also represents a key model system for analyzing complex cellular information processing and a starting point for understanding the complete regulatory network of an entire cell.

The sigma(s) subunit of RNA polymerase (RNAP) is the master regulator of the general stress response in Escherichia coli. Nevertheless, the selectivity of promoter recognition by the housekeeping sigma70-containing and sigma5-containing RNAP holoenzymes (Esigma70 and Esigma(s) respectively) is not yet fully clarified, as they both recognize nearly identical -35 and -10 promoter consensus sequences. In this study, we show that in a subset of promoters, Esigma(s) favours the presence of a distal UP-element half-site, and at the same time is unable to take advantage of a proximal half-site or a full UP-element. This is reflected by the frequent occurrence of distal UP-element half-sites in natural sigma(s)-dependent promoters and the absence of proximal half-sites. Esigma70, however, exhibits the opposite preference. The presence of the -35 element is a prerequisite for this differential behaviour. In the absence of the -35 element, half or full UP-element sites play no role in sigma selectivity, but the distal subsite leads to an equivalent, if not greater, transcriptional stimulation than the proximal one for both sigma factors. Finally, experiments using single amino acid substitutions of sigma(s) indicate that the foundation for this preference lies in an inability of sigma(s) to interact with the a subunit C-terminal domain.