Identification of type VI secretion system effector-immunity pairs using structural bioinformatics.

The type VI secretion system (T6SS) is an important mediator of microbe-microbe and microbe-host interactions. Gram-negative bacteria use the T6SS to inject T6SS effectors (T6Es), which are usually proteins with toxic activity, into neighboring cells. Antibacterial effectors have cognate immunity proteins that neutralize self-intoxication. Here, we applied novel structural bioinformatic tools to perform systematic discovery and functional annotation of T6Es and their cognate immunity proteins from a dataset of 17,920 T6SS-encoding bacterial genomes. Using structural clustering, we identified 517 putative T6E families, outperforming sequence-based clustering. We developed a logistic regression model to reliably quantify protein-protein interaction of new T6E-immunity pairs, yielding candidate immunity proteins for 231 out of the 517 T6E families. We used sensitive structure-based annotation which yielded functional annotations for 51% of the T6E families, again outperforming sequence-based annotation. Next, we validated four novel T6E-immunity pairs using basic experiments in E. coli. In particular, we showed that the Pfam domain DUF3289 is a homolog of Colicin M and that DUF943 acts as its cognate immunity protein. Furthermore, we discovered a novel T6E that is a structural homolog of SleB, a lytic transglycosylase, and identified a specific glutamate that acts as its putative catalytic residue. Overall, this study applies novel structural bioinformatic tools to T6E-immunity pair discovery, and provides an extensive database of annotated T6E-immunity pairs.

Toxinome-the bacterial protein toxin database.

IMPORTANCE: Microbes use protein toxins as important tools to attack neighboring cells, microbial or eukaryotic, and for self-killing when attacked by viruses. These toxins work through different mechanisms to inhibit cell growth or kill cells. Microbes also use antitoxin proteins to neutralize the toxin activities. Here, we developed a comprehensive database called Toxinome of nearly two million toxins and antitoxins that are encoded in 59,475 bacterial genomes. We described the distribution of bacterial toxins and identified that they are depleted by bacteria that live in hot and cold temperatures. We found 5,161 cases in which toxins and antitoxins are densely clustered in bacterial genomes and termed these areas "Toxin Islands." The Toxinome database is a useful resource for anyone interested in toxin biology and evolution, and it can guide the discovery of new toxins.

Comparative genomic analysis reveals differential genomic characteristics and featured genes between rapid- and slow-growing non-tuberculous mycobacteria.

Introduction: Non-tuberculous mycobacteria (NTM) is a major category of environmental bacteria in nature that can be divided into rapidly growing mycobacteria (RGM) and slowly growing mycobacteria (SGM) based on their distinct growth rates. To explore differential molecular mechanisms between RGM and SGM is crucial to understand their survival state, environmental/host adaptation and pathogenicity. Comparative genomic analysis provides a powerful tool for deeply investigating differential molecular mechanisms between them. However, large-scale comparative genomic analysis between RGM and SGM is still uncovered. Methods: In this study, we screened 335 high-quality, non-redundant NTM genome sequences covering 187 species from 3,478 online NTM genomes, and then performed a comprehensive comparative genomic analysis to identify differential genomic characteristics and featured genes/protein domains between RGM and SGM. Results: Our findings reveal that RGM has a larger genome size, more genes, lower GC content, and more featured genes/protein domains in metabolism of some main substances (e.g. carbohydrates, amino acids, nucleotides, ions, and coenzymes), energy metabolism, signal transduction, replication, transcription, and translation processes, which are essential for its rapid growth requirements. On the other hand, SGM has a smaller genome size, fewer genes, higher GC content, and more featured genes/protein domains in lipid and secondary metabolite metabolisms and cellular defense mechanisms, which help enhance its genome stability and environmental adaptability. Additionally, orthogroup analysis revealed the important roles of bacterial division and bacteriophage associated genes in RGM and secretion system related genes for better environmental adaptation in SGM. Notably, PCoA analysis of the top 20 genes/protein domains showed precision classification between RGM and SGM, indicating the credibility of our screening/classification strategies. Discussion: Overall, our findings shed light on differential underlying molecular mechanisms in survival state, adaptation and pathogenicity between RGM and SGM, show the potential for our comparative genomic pipeline to investigate differential genes/protein domains at whole genomic level across different bacterial species on a large scale, and provide an important reference and improved understanding of NTM.

"What I cannot create, I do not understand": elucidating microbe-microbe interactions to facilitate plant microbiome engineering.

Plant-microbe interactions are important for both physiological and pathological processes. Despite the significance of plant-microbe interactions, microbe-microbe interactions themselves represent an important, complex, dynamic network that warrants deeper investigation. To understand how microbe-microbe interactions affect plant microbiomes, one approach is to systematically understand all the factors involved in successful engineering of a microbial community. This follows the physicist Richard Feynman's declaration: "what I cannot create, I do not understand". This review highlights recent studies that focus on aspects that we believe are important for building (ergo understanding) microbe-microbe interactions in the plant environment, including pairwise screening, intelligent application of cross-feeding models, spatial distributions of microbes, and understudied interactions between bacteria and fungi, phages, and protists. We offer a framework for systematic collection and centralized integration of data of plant microbiomes that could organize all the factors that can help ecologists understand microbiomes and help synthetic ecologists engineer beneficial microbiomes.

Cell-Cell Signaling Proteobacterial LuxR Solos: a Treasure Trove of Subgroups Having Different Origins, Ligands, and Ecological Roles.

Many proteobacteria possess LuxR solos which are quorum sensing LuxR-type regulators that are not paired with a cognate LuxI-type synthase. LuxR solos have been implicated in intraspecies, interspecies, and interkingdom communication by sensing endogenous and exogenous acyl-homoserine lactones (AHLs) as well as non-AHL signals. LuxR solos are likely to play a major role in microbiome formation, shaping, and maintenance through many different cell-cell signaling mechanisms. This review intends to assess the different types and discuss the possible functional roles of the widespread family of LuxR solo regulators. In addition, an analysis of LuxR solo types and variability among the totality of publicly available proteobacterial genomes is presented. This highlights the importance of these proteins and will encourage scientists to mobilize and study them in order to increase our knowledge of novel cell-cell mechanisms that drive bacterial interactions in the context of complex bacterial communities.

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC-ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

The extracellular contractile injection system is enriched in environmental microbes and associates with numerous toxins.

The extracellular Contractile Injection System (eCIS) is a toxin-delivery particle that evolved from a bacteriophage tail. Four eCISs have previously been shown to mediate interactions between bacteria and their invertebrate hosts. Here, we identify eCIS loci in 1,249 bacterial and archaeal genomes and reveal an enrichment of these loci in environmental microbes and their apparent absence from mammalian pathogens. We show that 13 eCIS-associated toxin genes from diverse microbes can inhibit the growth of bacteria and/or yeast. We identify immunity genes that protect bacteria from self-intoxication, further supporting an antibacterial role for some eCISs. We also identify previously undescribed eCIS core genes, including a conserved eCIS transcriptional regulator. Finally, we present our data through an extensive eCIS repository, termed eCIStem. Our findings support eCIS as a toxin-delivery system that is widespread among environmental prokaryotes and likely mediates antagonistic interactions with eukaryotes and other prokaryotes.

The Breadth and Molecular Basis of Hcp-Driven Type VI Secretion System Effector Delivery.

The type VI secretion system (T6SS) is a bacterial nanoscale weapon that delivers toxins into prey ranging from bacteria and fungi to animal hosts. The cytosolic contractile sheath of the system wraps around stacked hexameric rings of Hcp proteins, which form an inner tube. At the tip of this tube is a puncturing device comprising a trimeric VgrG topped by a monomeric PAAR protein. The number of toxins a single system delivers per firing event remains unknown, since effectors can be loaded on diverse sites of the T6SS apparatus, notably the inner tube and the puncturing device. Each VgrG or PAAR can bind one effector, and additional effector cargoes can be carried in the Hcp ring lumen. While many VgrG- and PAAR-bound toxins have been characterized, to date, very few Hcp-bound effectors are known. Here, we used 3 known Pseudomonas aeruginosa Hcp proteins (Hcp1 to -3), each of which associates with one of the three T6SSs in this organism (H1-T6SS, H2-T6SS, and H3-T6SS), to perform in vivo pulldown assays. We confirmed the known interactions of Hcp1 with Tse1 to -4, further copurified a Hcp1-Tse4 complex, and identified potential novel Hcp1-bound effectors. Moreover, we demonstrated that Hcp2 and Hcp3 can shuttle T6SS cargoes toxic to Escherichia coli. Finally, we used a Tse1-Bla chimera to probe the loading strategy for Hcp passengers and found that while large effectors can be loaded onto Hcp, the formed complex jams the system, abrogating T6SS function. IMPORTANCE The type VI secretion system (T6SS) is an effective weapon used by bacteria to outgrow or kill competitors. It can be used by endogenous commensal microbiota to prevent invasion by pathogens or by pathogens to overcome resident flora and successfully colonize a host or a specific environmental niche. The T6SS is a key contributor to this continuous arms race between organisms as it delivers a multitude of toxins directed at essential processes, such as nucleic acid synthesis and replication, cell wall and membrane integrity, protein synthesis, or cofactor abundance. Many T6SS toxins with unknown function remain to be discovered, whose yet-uncharacterized targets could be exploited for antimicrobial drug design. The systematic search for these toxins is not facilitated by the presence of readily recognizable T6SS motifs, and unbiased screening approaches are thus required. Here, we successfully used a known shuttle for cargo T6SS effectors, Hcp, as bait to identify uncharacterized toxins.

The Role of Secretion Systems, Effectors, and Secondary Metabolites of Beneficial Rhizobacteria in Interactions With Plants and Microbes.

Beneficial rhizobacteria dwell in plant roots and promote plant growth, development, and resistance to various stress types. In recent years there have been large-scale efforts to culture root-associated bacteria and sequence their genomes to uncover novel beneficial microbes. However, only a few strains of rhizobacteria from the large pool of soil microbes have been studied at the molecular level. This review focuses on the molecular basis underlying the phenotypes of three beneficial microbe groups; (1) plant-growth promoting rhizobacteria (PGPR), (2) root nodulating bacteria (RNB), and (3) biocontrol agents (BCAs). We focus on bacterial proteins and secondary metabolites that mediate known phenotypes within and around plants, and the mechanisms used to secrete these. We highlight the necessity for a better understanding of bacterial genes responsible for beneficial plant traits, which can be used for targeted gene-centered and molecule-centered discovery and deployment of novel beneficial rhizobacteria.

LuxR Solos in the Plant Endophyte Kosakonia sp. Strain KO348.

Endophytes are microorganisms that live inside plants and are often beneficial for the host. Kosakonia is a novel bacterial genus that includes several species that are diazotrophic and plant associated. This study revealed two quorum sensing-related LuxR solos, designated LoxR and PsrR, in the plant endophyte Kosakonia sp. strain KO348. LoxR modeling and biochemical studies demonstrated that LoxR binds N-acyl homoserine lactones (AHLs) in a promiscuous way. PsrR, on the other hand, belongs to the subfamily of plant-associated-bacterium (PAB) LuxR solos that respond to plant compounds. Target promoter studies as well as modeling and phylogenetic comparisons suggest that PAB LuxR solos are likely to respond to different plant compounds. Finally, LoxR is involved in the regulation of T6SS and PsrR plays a role in root endosphere colonization.IMPORTANCE Cell-cell signaling in bacteria allows a synchronized and coordinated behavior of a microbial community. LuxR solos represent a subfamily of proteins in proteobacteria which most commonly detect and respond to signals produced exogenously by other microbes or eukaryotic hosts. Here, we report that a plant-beneficial bacterial endophyte belonging to the novel genus of Kosakonia possesses two LuxR solos; one is involved in the detection of exogenous N-acyl homoserine lactone quorum sensing signals and the other in detecting a compound(s) produced by the host plant. These two Kosakonia LuxR solos are therefore most likely involved in interspecies and interkingdom signaling.

AzeR, a transcriptional regulator that responds to azelaic acid in Pseudomonas nitroreducens.

Azelaic acid is a dicarboxylic acid that has recently been shown to play a role in plant-bacteria signalling and also occurs naturally in several cereals. Several bacteria have been reported to be able to utilize azelaic acid as a unique source of carbon and energy, including Pseudomonas nitroreducens. In this study, we utilize P. nitroreducens as a model organism to study bacterial degradation of and response to azelaic acid. We report genetic evidence of azelaic acid degradation and the identification of a transcriptional regulator that responds to azelaic acid in P. nitroreducens DSM 9128. Three mutants possessing transposons in genes of an acyl-CoA ligase, an acyl-CoA dehydrogenase and an isocitrate lyase display a deficient ability in growing in azelaic acid. Studies on transcriptional regulation of these genes resulted in the identification of an IclR family repressor that we designated as AzeR, which specifically responds to azelaic acid. A bioinformatics survey reveals that AzeR is confined to a few proteobacterial genera that are likely to be able to degrade and utilize azelaic acid as the sole source of carbon and energy.

In Planta Colonization and Role of T6SS in Two Rice Kosakonia Endophytes.

Endophytes live inside plants and are often beneficial. Kosakonia is a novel bacterial genus that includes many diazotrophic plant-associated isolates. Plant-bacteria studies on two rice endophytic Kosakonia beneficial strains were performed, including comparative genomics, secretome profiling, in planta tests, and a field release trial. The strains are efficient rhizoplane and root endosphere colonizers and localized in the root cortex. Secretomics revealed 144 putative secreted proteins, including type VI secretory system (T6SS) proteins. A Kosakonia T6SS genomic knock-out mutant showed a significant decrease in rhizoplane and endosphere colonization ability. A field trial using rice seed inoculated with Kosakonia spp. showed no effect on plant growth promotion upon nitrogen stress and microbiome studies revealed that Kosakonia spp. were significantly more present in the inoculated rice. Comparative genomics indicated that several protein domains were enriched in plant-associated Kosakonia spp. This study highlights that Kosakonia is an important, recently classified genus involved in plant-bacteria interaction.

Elucidating Bacterial Gene Functions in the Plant Microbiome.

There is a growing appreciation for the important roles microorganisms play in association with plants. Microorganisms are drawn to distinct plant surfaces by the nutrient-rich microenvironment, and in turn some of these colonizing microbes provide mutualistic benefits to their host. The development of plant probiotics to increase crop yield and provide plant resistance against biotic and abiotic stresses, while minimizing chemical inputs, would benefit from a deeper mechanistic understanding of plant-microbe interaction. Technological advances in molecular biology and high-throughput -omics provide stepping stones to the elucidation of critical microbiome gene functions that aid in improving plant performance. Here, we review -omics-based approaches that are propelling forward the current understanding of plant-associated bacterial gene functions, and describe how these technologies have helped unravel key bacterial genes and pathways that mediate pathogenic, beneficial, and commensal host interactions.

Genomic features of bacterial adaptation to plants.

Plants intimately associate with diverse bacteria. Plant-associated bacteria have ostensibly evolved genes that enable them to adapt to plant environments. However, the identities of such genes are mostly unknown, and their functions are poorly characterized. We sequenced 484 genomes of bacterial isolates from roots of Brassicaceae, poplar, and maize. We then compared 3,837 bacterial genomes to identify thousands of plant-associated gene clusters. Genomes of plant-associated bacteria encode more carbohydrate metabolism functions and fewer mobile elements than related non-plant-associated genomes do. We experimentally validated candidates from two sets of plant-associated genes: one involved in plant colonization, and the other serving in microbe-microbe competition between plant-associated bacteria. We also identified 64 plant-associated protein domains that potentially mimic plant domains; some are shared with plant-associated fungi and oomycetes. This work expands the genome-based understanding of plant-microbe interactions and provides potential leads for efficient and sustainable agriculture through microbiome engineering.

Natural selection underlies apparent stress-induced mutagenesis in a bacteriophage infection model.

The emergence of mutations following growth-limiting conditions underlies bacterial drug resistance, viral escape from the immune system and fundamental evolution-driven events. Intriguingly, whether mutations are induced by growth limitation conditions or are randomly generated during growth and then selected by growth limitation conditions remains an open question(1). Here, we show that bacteriophage T7 undergoes apparent stress-induced mutagenesis when selected for improved recognition of its host's receptor. In our unique experimental set-up, the growth limitation condition is physically and temporally separated from mutagenesis: growth limitation occurs while phage DNA is outside the host, and spontaneous mutations occur during phage DNA replication inside the host. We show that the selected beneficial mutations are not pre-existing and that the initial slow phage growth is enabled by the phage particle's low-efficiency DNA injection into the host. Thus, the phage particle allows phage populations to initially extend their host range without mutagenesis by virtue of residual recognition of the host receptor. Mutations appear during non-selective intracellular replication, and the frequency of mutant phages increases by natural selection acting on free phages, which are not capable of mutagenesis.

Toxin-Antitoxin systems eliminate defective cells and preserve symmetry in Bacillus subtilis biofilms.

Toxin-antitoxin modules are gene pairs encoding a toxin and its antitoxin, and are found on the chromosomes of many bacteria, including pathogens. Here, we characterize the specific contribution of the TxpA and YqcG toxins in elimination of defective cells from developing Bacillus subtilis biofilms. On nutrient limitation, defective cells accumulated in the biofilm breaking its symmetry. Deletion of the toxins resulted in accumulation of morphologically abnormal cells, and interfered with the proper development of the multicellular community. Dual physiological responses are of significance for TxpA and YqcG activation: nitrogen deprivation enhances the transcription of both TxpA and YqcG toxins, and simultaneously sensitizes the biofilm cells to their activity. Furthermore, we demonstrate that while both toxins when overexpressed affect the morphology of the developing biofilm, the toxin TxpA can act to lyse and dissolve pre-established B. subtilis biofilms.

High-resolution phylogenetic microbial community profiling.

Over the past decade, high-throughput short-read 16S rRNA gene amplicon sequencing has eclipsed clone-dependent long-read Sanger sequencing for microbial community profiling. The transition to new technologies has provided more quantitative information at the expense of taxonomic resolution with implications for inferring metabolic traits in various ecosystems. We applied single-molecule real-time sequencing for microbial community profiling, generating full-length 16S rRNA gene sequences at high throughput, which we propose to name PhyloTags. We benchmarked and validated this approach using a defined microbial community. When further applied to samples from the water column of meromictic Sakinaw Lake, we show that while community structures at the phylum level are comparable between PhyloTags and Illumina V4 16S rRNA gene sequences (iTags), variance increases with community complexity at greater water depths. PhyloTags moreover allowed less ambiguous classification. Last, a platform-independent comparison of PhyloTags and in silico generated partial 16S rRNA gene sequences demonstrated significant differences in community structure and phylogenetic resolution across multiple taxonomic levels, including a severe underestimation in the abundance of specific microbial genera involved in nitrogen and methane cycling across the Lake's water column. Thus, PhyloTags provide a reliable adjunct or alternative to cost-effective iTags, enabling more accurate phylogenetic resolution of microbial communities and predictions on their metabolic potential.

Uncultivated thermophiles: current status and spotlight on 'Aigarchaeota'.

Meta-analysis of cultivation-independent sequence data shows that geothermal systems host an abundance of novel organisms, representing a vast unexplored phylogenetic and functional diversity among yet-uncultivated thermophiles. A number of thermophiles have recently been interrogated using metagenomic and/or single-cell genomic approaches, including members of taxonomic groups that inhabit both thermal and non-thermal environments, such as 'Acetothermia' (OP1) and 'Atribacteria' (OP9/JS1), as well as the exclusively thermophilic lineages 'Korarchaeota', 'Calescamantes' (EM19), 'Fervidibacteria' (OctSpA1-106), and 'Aigarchaeota' (HWCG-I). The 'Aigarchaeota', a sister lineage to the Thaumarchaeota, likely includes both hyperthermophiles and moderate thermophiles. They inhabit terrestrial, marine, and subsurface thermal environments and comprise at least nine genus-level lineages, several of which are globally distributed.

CRISPR adaptation biases explain preference for acquisition of foreign DNA.

CRISPR-Cas (clustered, regularly interspaced short palindromic repeats coupled with CRISPR-associated proteins) is a bacterial immunity system that protects against invading phages or plasmids. In the process of CRISPR adaptation, short pieces of DNA ('spacers') are acquired from foreign elements and integrated into the CRISPR array. So far, it has remained a mystery how spacers are preferentially acquired from the foreign DNA while the self chromosome is avoided. Here we show that spacer acquisition is replication-dependent, and that DNA breaks formed at stalled replication forks promote spacer acquisition. Chromosomal hotspots of spacer acquisition were confined by Chi sites, which are sequence octamers highly enriched on the bacterial chromosome, suggesting that these sites limit spacer acquisition from self DNA. We further show that the avoidance of self is mediated by the RecBCD double-stranded DNA break repair complex. Our results suggest that, in Escherichia coli, acquisition of new spacers largely depends on RecBCD-mediated processing of double-stranded DNA breaks occurring primarily at replication forks, and that the preference for foreign DNA is achieved through the higher density of Chi sites on the self chromosome, in combination with the higher number of forks on the foreign DNA. This model explains the strong preference to acquire spacers both from high copy plasmids and from phages.

Transcriptome profiling of khat (Catha edulis) and Ephedra sinica reveals gene candidates potentially involved in amphetamine-type alkaloid biosynthesis.

Amphetamine analogues are produced by plants in the genus Ephedra and by khat (Catha edulis), and include the widely used decongestants and appetite suppressants (1S,2S)-pseudoephedrine and (1R,2S)-ephedrine. The production of these metabolites, which derive from L-phenylalanine, involves a multi-step pathway partially mapped out at the biochemical level using knowledge of benzoic acid metabolism established in other plants, and direct evidence using khat and Ephedra species as model systems. Despite the commercial importance of amphetamine-type alkaloids, only a single step in their biosynthesis has been elucidated at the molecular level. We have employed Illumina next-generation sequencing technology, paired with Trinity and Velvet-Oases assembly platforms, to establish data-mining frameworks for Ephedra sinica and khat plants. Sequence libraries representing a combined 200,000 unigenes were subjected to an annotation pipeline involving direct searches against public databases. Annotations included the assignment of Gene Ontology (GO) terms used to allocate unigenes to functional categories. As part of our functional genomics program aimed at novel gene discovery, the databases were mined for enzyme candidates putatively involved in alkaloid biosynthesis. Queries used for mining included enzymes with established roles in benzoic acid metabolism, as well as enzymes catalyzing reactions similar to those predicted for amphetamine alkaloid metabolism. Gene candidates were evaluated based on phylogenetic relationships, FPKM-based expression data, and mechanistic considerations. Establishment of expansive sequence resources is a critical step toward pathway characterization, a goal with both academic and industrial implications.