Vibrio fischeri: a model for host-associated biofilm formation.

Multicellular communities of adherent bacteria known as biofilms are often detrimental in the context of a human host, making it important to study their formation and dispersal, especially in animal models. One such model is the symbiosis between the squid Euprymna scolopes and the bacterium Vibrio fischeri. Juvenile squid hatch aposymbiotically and selectively acquire their symbiont from natural seawater containing diverse environmental microbes. Successful pairing is facilitated by ciliary movements that direct bacteria to quiet zones on the surface of the squid's symbiotic light organ where V. fischeri forms a small aggregate or biofilm. Subsequently, the bacteria disperse from that aggregate to enter the organ, ultimately reaching and colonizing deep crypt spaces. Although transient, aggregate formation is critical for optimal colonization and is tightly controlled. In vitro studies have identified a variety of polysaccharides and proteins that comprise the extracellular matrix. Some of the most well-characterized matrix factors include the symbiosis polysaccharide (SYP), cellulose polysaccharide, and LapV adhesin. In this review, we discuss these components, their regulation, and other less understood V. fischeri biofilm contributors. We also highlight what is currently known about dispersal from these aggregates and host cues that may promote it. Finally, we briefly describe discoveries gleaned from the study of other V. fischeri isolates. By unraveling the complexities involved in V. fischeri's control over matrix components, we may begin to understand how the host environment triggers transient biofilm formation and dispersal to promote this unique symbiotic relationship.

Streptococcus pyogenes TrxSR Two-Component System Regulates Biofilm Production in Acidic Environments.

Bacteria form biofilms for their protection against environmental stress and produce virulence factors within the biofilm. Biofilm formation in acidified environments is regulated by a two-component system, as shown by studies on isogenic mutants of the sensor protein of the two-component regulatory system in Streptococcus pyogenes. In this study, we found that the LiaS histidine kinase sensor mediates biofilm production and pilus expression in an acidified environment through glucose fermentation. The liaS isogenic mutant produced biofilms in a culture acidified by hydrochloric acid but not glucose, suggesting that the acidified environment is sensed by another protein. In addition, the trxS isogenic mutant could not produce biofilms or activate the mga promoter in an acidified environment. Mass spectrometry analysis showed that TrxS regulates M protein, consistent with the transcriptional regulation of emm, which encodes M protein. Our results demonstrate that biofilm production during environmental acidification is directly under the control of TrxS.

Conformational Changes of an Interdomain Linker Mediate Mechanical Signal Transmission in Sensor Kinase BvgS.

The whooping cough agent, Bordetella pertussis, controls the expression of its large virulence regulon in a coordinated manner through the two-component system BvgAS. BvgS is a dimeric, multidomain sensor kinase. Each monomer comprises, in succession, tandem periplasmic Venus flytrap (VFT) domains, a transmembrane segment, a cytoplasmic Per-Arnt-Sim (PAS) domain, a kinase module, and additional phosphorelay domains. BvgS shifts between kinase and phosphatase modes of activity in response to chemical modulators that modify the clamshell motions of the VFT domains. We have shown previously that this regulation involves a shift between distinct states of conformation and dynamics of the two-helix coiled-coil linker preceding the enzymatic module. In this work, we determined the mechanism of signal transduction across the membrane via a first linker, which connects the VFT and PAS domains of BvgS, using extensive cysteine cross-linking analyses and other approaches. Modulator perception by the periplasmic domains appears to trigger a small, symmetrical motion of the transmembrane segments toward the periplasm, causing rearrangements of the noncanonical cytoplasmic coiled coil that follows. As a consequence, the interface of the PAS domains is modified, which affects the second linker and eventually causes the shift of enzymatic activity. The major features of this first linker are well conserved among BvgS homologs, indicating that the mechanism of signal transduction unveiled here is likely to be generally relevant for this family of sensor kinases.IMPORTANCEBordetella pertussis produces virulence factors coordinately regulated by the two-component system BvgAS. BvgS is a sensor kinase, and BvgA is a response regulator that activates gene transcription when phosphorylated by BvgS. Sensor kinases homologous to BvgS are also found in other pathogens. Our goal is to decipher the mechanisms of BvgS signaling, since these sensor kinases may represent new targets for antibacterial agents. Signal perception by the sensor domains of BvgS triggers small motions of the helical linker region underneath. The protein domain that follows this linker undergoes a large conformational change that amplifies the initial signal, causing a shift of activity from kinase to phosphatase. Because BvgS homologs harbor similar regions, these signaling mechanisms are likely to apply generally to that family of sensor kinases.

A bacterial sensor taxonomy across earth ecosystems for machine learning applications.

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Phylogenetic Analysis with Prediction of Cofactor or Ligand Binding for Pseudomonas aeruginosa PAS and Cache Domains.

PAS domains are omnipresent building blocks of multidomain proteins in all domains of life. Bacteria possess a variety of PAS domains in intracellular proteins and the related Cache domains in periplasmic or extracellular proteins. PAS and Cache domains are predominant in sensory systems, often carry cofactors or bind ligands, and serve as dimerization domains in protein association. To aid our understanding of the wide distribution of these domains, we analyzed the proteome of the opportunistic human pathogen Pseudomonas aeruginosa PAO1 in silico. The ability of this bacterium to survive under different environmental conditions, to switch between planktonic and sessile/biofilm lifestyle, or to evade stresses, notably involves c-di-GMP regulatory proteins or depends on sensory pathways involving multidomain proteins that possess PAS or Cache domains. Maximum likelihood phylogeny was used to group PAS and Cache domains on the basis of amino acid sequence. Conservation of cofactor- or ligand-coordinating amino acids aided by structure-based comparison was used to inform function. The resulting classification presented here includes PAS domains that are candidate binders of carboxylic acids, amino acids, fatty acids, flavin adenine dinucleotide (FAD), 4-hydroxycinnamic acid, and heme. These predictions are put in context to previously described phenotypic data, often generated from deletion mutants. The analysis predicts novel functions for sensory proteins and sheds light on functional diversification in a large set of proteins with similar architecture. IMPORTANCE To adjust to a variety of life conditions, bacteria typically use multidomain proteins, where the modular structure allows functional differentiation. Proteins responding to environmental cues and regulating physiological responses are found in chemotaxis pathways that respond to a wide range of stimuli to affect movement. Environmental cues also regulate intracellular levels of cyclic-di-GMP, a universal bacterial secondary messenger that is a key determinant of bacterial lifestyle and virulence. We study Pseudomonas aeruginosa, an organism known to colonize a broad range of environments that can switch lifestyle between the sessile biofilm and the planktonic swimming form. We have investigated the PAS and Cache domains, of which we identified 101 in 70 Pseudomonas aeruginosa PAO1 proteins, and have grouped these by phylogeny with domains of known structure. The resulting data set integrates sequence analysis and structure prediction to infer ligand or cofactor binding. With this data set, functional predictions for PAS and Cache domain-containing proteins are made.

An Aspartate-Specific Solute-Binding Protein Regulates Protein Kinase G Activity To Control Glutamate Metabolism in Mycobacteria.

Signaling by serine/threonine phosphorylation controls diverse processes in bacteria, and identification of the stimuli that activate protein kinases is an outstanding question in the field. Recently, we showed that nutrients stimulate phosphorylation of the protein kinase G substrate GarA in Mycobacterium smegmatis and Mycobacterium tuberculosis and that the action of GarA in regulating central metabolism depends upon whether it is phosphorylated. Here we present an investigation into the mechanism by which nutrients activate PknG. Two unknown genes were identified as co-conserved and co-expressed with PknG: their products were a putative lipoprotein, GlnH, and putative transmembrane protein, GlnX. Using a genetic approach, we showed that the membrane protein GlnX is functionally linked to PknG. Furthermore, we determined that the ligand specificity of GlnH matches the amino acids that stimulate GarA phosphorylation. We determined the structure of GlnH in complex with different amino acid ligands (aspartate, glutamate, and asparagine), revealing the structural basis of ligand specificity. We propose that the amino acid concentration in the periplasm is sensed by GlnH and that protein-protein interaction allows transmission of this information across the membrane via GlnX to activate PknG. This sensory system would allow regulation of nutrient utilization in response to changes in nutrient availability. The sensor, signaling, and effector proteins are conserved throughout the Actinobacteria, including the important human pathogen Mycobacterium tuberculosis, industrial amino acid producer Corynebacterium glutamicum, and antibiotic-producing Streptomyces species.IMPORTANCE Tuberculosis (TB) kills 5,000 people every day, and the prevalence of multidrug-resistant TB is increasing in every country. The processes by which the pathogen Mycobacterium tuberculosis senses and responds to changes in its environment are attractive targets for drug development. Bacterial metabolism differs dramatically between growing and dormant cells, and these changes are known to be important in pathogenesis of TB. Here, we used genetic and biochemical approaches to identify proteins that allow M. tuberculosis to detect amino acids in its surroundings so that it can regulate its metabolism. We have also shown how individual amino acids are recognized. The findings have broader significance for other actinobacterial pathogens, such as nontuberculous mycobacteria, as well as Actinobacteria used to produce billions of dollars of amino acids and antibiotics every year.