Unique mobile elements and scalable gene flow at the prokaryote–eukaryote boundary revealed by circularized Asgard archaea genomes

Eukaryotic genomes are known to have garnered innovations from both archaeal and bacterial domains but the sequence of events that led to the complex gene repertoire of eukaryotes is largely unresolved. Here, through the enrichment of hydrothermal vent microorganisms, we recovered two circularized genomes of Heimdallarchaeum species that belong to an Asgard archaea clade phylogenetically closest to eukaryotes. These genomes reveal diverse mobile elements, including an integrative viral genome that bidirectionally replicates in a circular form and aloposons, transposons that encode the 5,000 amino acid-sized proteins Otus and Ephialtes. Heimdallaechaeal mobile elements have garnered various genes from bacteria and bacteriophages, likely playing a role in shuffling functions across domains. The number of archaea- and bacteria-related genes follow strikingly different scaling laws in Asgard archaea, exhibiting a genome size-dependent ratio and a functional division resembling the bacteria- and archaea-derived gene repertoire across eukaryotes. Bacterial gene import has thus likely been a continuous process unaltered by eukaryogenesis and scaled up through genome expansion. Our data further highlight the importance of viewing eukaryogenesis in a pan-Asgard context, which led to the proposal of a conceptual framework, that is, the Heimdall nucleation–decentralized innovation–hierarchical import model that accounts for the emergence of eukaryotic complexity.

Machine-learning from Pseudomonas putida transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1,993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

Affinity, Specificity, and Cooperativity of DNA Binding by Bacterial Gene Regulatory Proteins

Nearly all of biology depends on interactions between molecules: proteins with small molecules, proteins with other proteins, nucleic acids with small molecules, and nucleic acids with proteins that regulate gene expression, our concern in this Special Issue. All those kinds of interactions, and others, constitute the vast majority of biology at the molecular level. An understanding of those interactions requires that we quantify them to learn how they interact: How strongly? With which partners? How—and how well—are different partners distinguished? This review addresses the evolution of our current understanding of the molecular origins of affinity and specificity in regulatory protein–DNA interactions, and suggests that both these properties can be modulated by cooperativity.

Using cryo-EM to uncover mechanisms of bacterial transcriptional regulation

Transcription is the principal control point for bacterial gene expression, and it enables a global cellular response to an intracellular or environmental trigger. Transcriptional regulation is orchestrated by transcription factors, which activate or repress transcription of target genes by modulating the activity of RNA polymerase. Dissecting the nature and precise choreography of these interactions is essential for developing a molecular understanding of transcriptional regulation. While the contribution of X-ray crystallography has been invaluable, the ‘resolution revolution’ of cryo-electron microscopy has transformed our structural investigations, enabling large, dynamic and often transient transcription complexes to be resolved that in many cases had resisted crystallisation. In this review, we highlight the impact cryo-electron microscopy has had in gaining a deeper understanding of transcriptional regulation in bacteria. We also provide readers working within the field with an overview of the recent innovations available for cryo-electron microscopy sample preparation and image reconstruction of transcription complexes.

The economy of chromosomal distances in bacterial gene regulation

In the transcriptional regulatory network (TRN) of a bacterium, the nodes are genes and a directed edge represents the action of a transcription factor (TF), encoded by the source gene, on the target gene. It is a condensed representation of a large number of biological observations and facts. Nonrandom features of the network are structural evidence of requirements for a reliable systemic function. For the bacterium Escherichia coli we here investigate the (Euclidean) distances covered by the edges in the TRN when its nodes are embedded in the real space of the circular chromosome. Our work is motivated by ’wiring economy’ research in Computational Neuroscience and starts from two contradictory hypotheses: (1) TFs are predominantly employed for long-distance regulation, while local regulation is exerted by chromosomal structure, locally coordinated by the action of structural proteins. Hence long distances should often occur. (2) A large distance between the regulator gene and its target requires a higher expression level of the regulator gene due to longer reaching times and ensuing increased degradation (proteolysis) of the TF and hence will be evolutionarily reduced. Our analysis supports the latter hypothesis.

Computational modelling of chromosomally clustering protein domains in bacteria

Background In bacteria, genes with related functions—such as those involved in the metabolism of the same compound or in infection processes—are often physically close on the genome and form groups called clusters. The enrichment of such clusters over various distantly related bacteria can be used to predict the roles of genes of unknown function that cluster with characterised genes. There is no obvious rule to define a cluster, given their variability in size and intergenic distances, and the definition of what comprises a “gene”, since genes can gain and lose domains over time. Protein domains can cluster within a gene, or in adjacent genes of related function, and in both cases these are chromosomally clustered. Here, we model the distances between pairs of protein domain coding regions across a wide range of bacteria and archaea via a probabilistic two component mixture model, without imposing arbitrary thresholds in terms of gene numbers or distances. Results We trained our model using matched gene ontology terms to label functionally related pairs and assess the stability of the parameters of the model across 14,178 archaeal and bacterial strains. We found that the parameters of our mixture model are remarkably stable across bacteria and archaea, except for endosymbionts and obligate intracellular pathogens. Obligate pathogens have smaller genomes, and although they vary, on average do not show noticeably different clustering distances; the main difference in the parameter estimates is that a far greater proportion of the genes sharing ontology terms are clustered. This may reflect that these genomes are enriched for complexes encoded by clustered core housekeeping genes, as a proportion of the total genes. Given the overall stability of the parameter estimates, we then used the mean parameter estimates across the entire dataset to investigate which gene ontology terms are most frequently associated with clustered genes. Conclusions Given the stability of the mixture model across species, it may be used to predict bacterial gene clusters that are shared across multiple species, in addition to giving insights into the evolutionary pressures on the chromosomal locations of genes in different species.

Human Milk-Based or Bovine Milk-Based Fortifiers Differentially Impact the Development of the Gut Microbiota of Preterm Infants

Background: Preterm infants are exposed to different dietary inputs during their hospitalization in the neonatal intensive care unit (NICU). These include human milk (HM), with a human milk-based (HMF) or a bovine milk-based (BMF) fortifier, or formula. Milk consumption and the type of fortification will cause changes in the gut microbiota structure of preterm infants. This study aimed to characterize the gut microbiota of PT infant according to the type of feeding and the type of HM fortification and its possible association with infant's growth.Methods: Ninety-seven infants born ≤33 wks of gestation or <1,500 g were followed during the hospitalization period in the NICU after birth until discharge. Clinical and dietary information was collected, including mode of delivery, pregnancy complications, mechanical ventilation, use of antibiotics, weight, and type and amount of milk consumed. To characterize the gut microbiota composition, weekly stool samples were collected from study participants. The V3–V4 region of the 16S rRNA bacterial gene was Sequenced using Illumina MiSeq technology.Results: After birth, black maternal race, corrected gestational age (GA) and exposure to pregnancy complications, had a significant effect on gut microbial diversity and the abundance of Enterococcus, Veillonella, Bifidobacterium, Enterobacter, and Bacteroides. Over the course of hospitalization, corrected GA and exposure to chorioamnionitis remained to have an effect on gut microbial composition. Two different enterotypes were found in the gut microbiota of preterm infants. One enriched in Escherichia-Shigella, and another enriched in uncharacterized Enterobacteriaceae, Klebsiella and Clostridium sensu stricto 1. Overall, HM and fortification with HMF were the most common feeding strategies. When consuming BMF, PT infants had higher growth rates than those consuming HMF. Milk and type of fortification were significantly associated with the abundance of Clostridium sensu stricto 1, Bifidobacterium and Lactobacillus.Conclusions: This observational study shows the significant association between milk consumption and the exposure to HMF or BMF fortification in the fecal microbiota composition of preterm infants. Additionally, these results show the effect of other perinatal factors in the establishment and development of PT infant's gut microbiota.

Mapping Molecular Recognition of β1,3-1,4-Glucans by a Surface Glycan-Binding Protein from the Human Gut Symbiont Bacteroides ovatus

With the knowledge of bacterial gene systems encoding proteins that target dietary carbohydrates as a source of nutrients and their importance for human health, major efforts are being made to understand carbohydrate recognition by various commensal bacteria. Here, we describe an integrative strategy that combines carbohydrate microarray technology with structural studies to further elucidate the molecular determinants of carbohydrate recognition by BoSGBP MLG -A, a key protein expressed at the surface of Bacteroides ovatus for utilization of mixed-linkage β1,3-1,4-glucans.

Coordinated bacterial and plant sulfur metabolism in Enterobacter sp. SA187–induced plant salt stress tolerance

Enterobacter sp. SA187 is a root endophytic bacterium that maintains growth and yield of plants under abiotic stress conditions. In this work, we compared the metabolic wirings of Arabidopsis and SA187 in the free-living and endophytic interaction states. The interaction of SA187 with Arabidopsis induced massive changes in bacterial gene expression for chemotaxis, flagellar biosynthesis, quorum sensing, and biofilm formation. Besides modification of the bacterial carbon and energy metabolism, various nutrient and metabolite transporters and the entire sulfur pathway were up-regulated. Under salt stress, Arabidopsis resembled plants under sulfate starvation but not when colonized by SA187, which reprogramed the sulfur regulon of Arabidopsis. In accordance, salt hypersensitivity of multiple Arabidopsis sulfur metabolism mutants was partially or completely rescued by SA187 as much as by the addition of sulfate, L-cysteine, or L-methionine. Many components of the sulfur metabolism that are localized in the chloroplast were partially rescued by SA187. Finally, salt-induced accumulation of reactive oxygen species as well as the hypersensitivity of LSU mutants were suppressed by SA187. LSUs encode a central regulator linking sulfur metabolism to chloroplast superoxide dismutase activity. The coordinated regulation of the sulfur metabolic pathways in both the beneficial microorganism and the host plant is required for salt stress tolerance in Arabidopsis and might be a common mechanism utilized by different beneficial microbes to mitigate the harmful effects of different abiotic stresses on plants.