Engineered CRISPR-OsCas12f1 and RhCas12f1 with robust activities and expanded target range for genome editing.

The type V-F CRISPR-Cas12f system is a strong candidate for therapeutic applications due to the compact size of the Cas12f proteins. In this work, we identify six uncharacterized Cas12f1 proteins with nuclease activity in mammalian cells from assembled bacterial genomes. Among them, OsCas12f1 (433 aa) from Oscillibacter sp. and RhCas12f1 (415 aa) from Ruminiclostridium herbifermentans, which respectively target 5' T-rich Protospacer Adjacent Motifs (PAMs) and 5' C-rich PAMs, show the highest editing activity. Through protein and sgRNA engineering, we generate enhanced OsCas12f1 (enOsCas12f1) and enRhCas12f1 variants, with 5'-TTN and 5'-CCD (D = not C) PAMs respectively, exhibiting much higher editing efficiency and broader PAMs, compared with the engineered variant Un1Cas12f1 (Un1Cas12f1_ge4.1). Furthermore, by fusing the destabilized domain with enOsCas12f1, we generate inducible-enOsCas12f1 and demonstate its activity in vivo by single adeno-associated virus delivery. Finally, dead enOsCas12f1-based epigenetic editing and gene activation can also be achieved in mammalian cells. This study thus provides compact gene editing tools for basic research with remarkable promise for therapeutic applications.

Transcription-translation of the Escherichia coli genome within artificial cells.

Here we created artificial cells in which information of the genome of living cells is expressed by the elements encoded in the genome. We confirmed that the system works normally within artificial cells, which paves the way for reconstructing living cells from biomolecules.

Construction and Validation of a Genome-Scale Metabolic Network of Thermotoga sp. Strain RQ7.

Thermotoga are anaerobic hyperthermophiles that have a deep lineage to the last universal ancestor and produce biological hydrogen gas accompanying cell growth. In recent years, systems-level approaches have been used to elucidate their metabolic capacities, by integrating mathematical modeling and experimental results. To assist biochemical engineering studies of T. sp. strain RQ7, this work aims at building a metabolic model of the bacterium that quantitatively simulates its metabolism at the genome scale. The constructed model, RQ7_iJG408, consists of 408 genes, 692 reactions, and 538 metabolites. Constraint-based flux balance analyses were used to simulate cell growth in both the complex and defined media. Quantitative comparison of the predicted and measured growth rates resulted in good agreements. This model serves as a foundation for an integrated biochemical description of T. sp. strain RQ7. It is a useful tool in designing growth media, identifying metabolic engineering strategies, and exploiting the physiological potentials of this biotechnologically significant organism.

Arrayed CRISPRi and quantitative imaging describe the morphotypic landscape of essential mycobacterial genes.

Mycobacterium tuberculosis possesses a large number of genes of unknown or predicted function, undermining fundamental understanding of pathogenicity and drug susceptibility. To address this challenge, we developed a high-throughput functional genomics approach combining inducible CRISPR-interference and image-based analyses of morphological features and sub-cellular chromosomal localizations in the related non-pathogen, M. smegmatis. Applying automated imaging and analysis to 263 essential gene knockdown mutants in an arrayed library, we derive robust, quantitative descriptions of bacillary morphologies consequent on gene silencing. Leveraging statistical-learning, we demonstrate that functionally related genes cluster by morphotypic similarity and that this information can be used to inform investigations of gene function. Exploiting this observation, we infer the existence of a mycobacterial restriction-modification system, and identify filamentation as a defining mycobacterial response to histidine starvation. Our results support the application of large-scale image-based analyses for mycobacterial functional genomics, simultaneously establishing the utility of this approach for drug mechanism-of-action studies.

Caused by the microorganism Mycobacterium tuberculosis, tuberculosis kills more people around the world than any other infectious disease. M. tuberculosis is also becoming increasingly resistant to treatments, which are particularly difficult for patients to complete. The M. tuberculosis genome carries about four thousand genes, with several hundred being vital for survival. Finding new ways to fight tuberculosis relies on understanding the exact role of these essential genes, but they are difficult to study in living bacteria. To investigate this question, de Wet et al. used the related, fast-dividing bacterial species called M. smegmatis as a model. Microscopic imaging was combined with CRISPR-interference ­ a method that temporarily disrupts expression of a specific gene ­ to examine how blocking an essential gene would affect the shape of the living microorganism. Experiments were conducted on a collection of 270 mutants, capturing single-cell data for hundreds of thousands of live bacteria. To analyze the data, a computational pipeline was built, which automatically clustered similar-shaped bacteria. These groups, or 'phenoprints', brought together genes of known and unknown roles; this indicated that these genes participate in similar biological networks ­ and, if unknown, hinted at their function. Finally, targeting essential genes with CRISPR-interference often yielded the same shape changes as blocking their encoded proteins with antibiotics. This suggests that phenoprints could be useful to understand the mode of action of potential new tuberculosis treatments. When applied to M. tuberculosis and other deadly bacteria, the approach developed by de Wet et al. might speed up drug development.

Complementary Tendencies in the Use of Regulatory Elements (Transcription Factors, Sigma Factors, and Riboswitches) in Bacteria and Archaea.

In prokaryotes, the key players in transcription initiation are sigma factors and transcription factors that bind to DNA to modulate the process, while premature transcription termination at the 5' end of the genes is regulated by attenuation and, in particular, by attenuation associated with riboswitches. In this study, we describe the distribution of these regulators across phylogenetic groups of bacteria and archaea and find that their abundance not only depends on the genome size, as previously described, but also varies according to the phylogeny of the organism. Furthermore, we observed a tendency for organisms to compensate for the low frequencies of a particular type of regulatory element (i.e., transcription factors) with a high frequency of other types of regulatory elements (i.e., sigma factors). This study provides a comprehensive description of the more abundant COG, KEGG, and Rfam families of transcriptional regulators present in prokaryotic genomes.IMPORTANCE In this study, we analyzed the relationship between the relative frequencies of the primary regulatory elements in bacteria and archaea, namely, transcription factors, sigma factors, and riboswitches. In bacteria, we reveal a compensatory behavior for transcription factors and sigma factors, meaning that in phylogenetic groups in which the relative number of transcription factors was low, we found a tendency for the number of sigma factors to be high and vice versa. For most of the phylogenetic groups analyzed here, except for Firmicutes and Tenericutes, a clear relationship with other mechanisms was not detected for transcriptional riboswitches, suggesting that their low frequency in most genomes does not constitute a significant impact on the global variety of transcriptional regulatory elements in prokaryotic organisms.

Repurposing the Streptococcus mutans CRISPR-Cas9 System to Understand Essential Gene Function.

A recent genome-wide screen identified ~300 essential or growth-supporting genes in the dental caries pathogen Streptococcus mutans. To be able to study these genes, we built a CRISPR interference tool around the Cas9 nuclease (Cas9Smu) encoded in the S. mutans UA159 genome. Using a xylose-inducible dead Cas9Smu with a constitutively active single-guide RNA (sgRNA), we observed titratable repression of GFP fluorescence that compared favorably to that of Streptococcus pyogenes dCas9 (Cas9Spy). We then investigated sgRNA specificity and proto-spacer adjacent motif (PAM) requirements. Interference by sgRNAs did not occur with double or triple base-pair mutations, or if single base-pair mutations were in the 3' end of the sgRNA. Bioinformatic analysis of >450 S. mutans genomes allied with in vivo assays revealed a similar PAM recognition sequence as Cas9Spy. Next, we created a comprehensive library of sgRNA plasmids that were directed at essential and growth-supporting genes. We discovered growth defects for 77% of the CRISPRi strains expressing sgRNAs. Phenotypes of CRISPRi strains, across several biological pathways, were assessed using fluorescence microscopy. A variety of cell structure anomalies were observed, including segregational instability of the chromosome, enlarged cells, and ovococci-to-rod shape transitions. CRISPRi was also employed to observe how silencing of cell wall glycopolysaccharide biosynthesis (rhamnose-glucose polysaccharide, RGP) affected both cell division and pathogenesis in a wax worm model. The CRISPRi tool and sgRNA library are valuable resources for characterizing essential genes in S. mutans, some of which could prove to be promising therapeutic targets.

Vaginal Microbiome of Pregnant Indian Women: Insights into the Genome of Dominant Lactobacillus Species.

The trillions of microorganisms residing in the human body display varying degrees of compositional and functional diversities within and between individuals and contribute significantly to host physiology and susceptibility to disease. Microbial species present in the vaginal milieu of reproductive age women showed a large personal component and varies widely in different ethnic groups at the taxonomic, genomic, and functional levels. Lactobacillus iners, L. crispatus, L. gasseri, L. jensenii, and L. johnsonii are most frequently detected bacterial species in the vaginal milieu of reproductive age women. However, we currently lack (i) an understanding of the baseline vaginal microbiota of reproductive age Indian women, (ii) the extent of taxonomic and functional variations of vaginal microbiota between individuals and (iii) the genomic repertoires of the dominant vaginal microbiota associated with the Indian subjects. In our study, we analyzed the metagenome of high vaginal swab (HVS) samples collected from 40 pregnant Indian women enrolled in the GARBH-Ini cohort. Composition and abundance of bacterial species was characterized by pyrosequencing 16S rRNA gene. We identified 3067 OTUs with ≥ 10 reads from four different bacterial phyla. Several species of lactobacilli were clustered into three community state types (CSTs). L. iners, L. crispatus, L. gasseri, and L. jensenii are the most frequently detected Lactobacillus species in the vaginal environment of Indian women. Other than Lactobacillus, several species of Halomonas were also identified in the vaginal environment of most of the women sampled. To gain genomic and functional insights, we isolated several Lactobacillus species from the HVS samples and explored their whole genome sequences by shotgun sequencing. We analyzed the genome of dominant Lactobacillus species, L. iners, L. crispatus, L. gasseri, and L. paragesseri to represent the CSTs and identify functions that may influence the composition of complex vaginal microbial ecology. This study reports for the first time the vaginal microbial ecology of Indian women and genomic insights into L. iners, L. crispatus, L. gasseri, and L. paragesseri commonly found in the genital tract of reproductive age women.

Metabolic and genetic basis for auxotrophies in Gram-negative species.

Auxotrophies constrain the interactions of bacteria with their environment, but are often difficult to identify. Here, we develop an algorithm (AuxoFind) using genome-scale metabolic reconstruction to predict auxotrophies and apply it to a series of available genome sequences of over 1,300 Gram-negative strains. We identify 54 auxotrophs, along with the corresponding metabolic and genetic basis, using a pangenome approach, and highlight auxotrophies conferring a fitness advantage in vivo. We show that the metabolic basis of auxotrophy is species-dependent and varies with 1) pathway structure, 2) enzyme promiscuity, and 3) network redundancy. Various levels of complexity constitute the genetic basis, including 1) deleterious single-nucleotide polymorphisms (SNPs), in-frame indels, and deletions; 2) single/multigene deletion; and 3) movement of mobile genetic elements (including prophages) combined with genomic rearrangements. Fourteen out of 19 predictions agree with experimental evidence, with the remaining cases highlighting shortcomings of sequencing, assembly, annotation, and reconstruction that prevent predictions of auxotrophies. We thus develop a framework to identify the metabolic and genetic basis for auxotrophies in Gram-negatives.

Biofilm Bacteria Use Stress Responses to Detect and Respond to Competitors.

Bacteria use complex regulatory networks to cope with stress, but the function of these networks in natural habitats is poorly understood. The competition sensing hypothesis states that bacterial stress response systems can serve to detect ecological competition, but studying regulatory responses in diverse communities is challenging. Here, we solve this problem by using differential fluorescence induction to screen the Salmonella Typhimurium genome for loci that respond, at the single-cell level, to life in biofilms with competing strains of S. Typhimurium and Escherichia coli. This screening reveals the presence of competing strains drives up the expression of genes associated with biofilm matrix production (CsgD pathway), epithelial invasion (SPI1 invasion system), and, finally, chemical efflux and antibiotic tolerance (TolC efflux pump and AadA aminoglycoside 3-adenyltransferase). We validate that these regulatory changes result in the predicted phenotypic changes in biofilm, mammalian cell invasion, and antibiotic tolerance. We further show that these responses arise via activation of major stress responses, providing direct support for the competition sensing hypothesis. Moreover, inactivation of the type VI secretion system (T6SS) of a competitor annuls the responses to competition, indicating that T6SS-derived cell damage activates these stress response systems. Our work shows that bacteria use stress responses to detect and respond to competition in a manner important for major phenotypes, including biofilm formation, virulence, and antibiotic tolerance.

Ecogenomics of the Marine Benthic Filamentous Cyanobacterium Adonisia.

Turfs are among the major benthic components of reef systems worldwide. The nearly complete genome sequences, basic physiological characteristics, and phylogenomic reconstruction of two phycobiliprotein-rich filamentous cyanobacteria strains isolated from turf assemblages from the Abrolhos Bank (Brazil) are investigated. Both Adonisia turfae CCMR0081T (= CBAS 745T) and CCMR0082 contain approximately 8 Mbp in genome size and experiments identified that both strains exhibit chromatic acclimation. Whereas CCMR0081T exhibits chromatic acclimation type 3 (CA3) regulating both phycocyanin (PC) and phycoerythrin (PE), CCMR0082 strain exhibits chromatic acclimation type 2 (CA2), in correspondence with genes encoding specific photosensors and regulators for PC and PE. Furthermore, a high number and diversity of secondary metabolite synthesis gene clusters were identified in both genomes, and they were able to grow at high temperatures (28 °C, with scant growth at 30 °C). These characteristics provide insights into their widespread distribution in reef systems.

Metabolic and Genomic Traits of Phytobeneficial Phenazine-Producing Pseudomonas spp. Are Linked to Rhizosphere Colonization in Arabidopsis thaliana and Solanum tuberosum.

Bacterial rhizosphere colonization is critical for phytobeneficial rhizobacteria such as phenazine-producing Pseudomonas spp. To better understand this colonization process, potential metabolic and genomic determinants required for rhizosphere colonization were identified using a collection of 60 phenazine-producing Pseudomonas strains isolated from multiple plant species and representative of the worldwide diversity. Arabidopsis thaliana and Solanum tuberosum (potato) were used as host plants. Bacterial rhizosphere colonization was measured by quantitative PCR using a newly designed primer pair and TaqMan probe targeting a conserved region of the phenazine biosynthetic operon. The metabolic abilities of the strains were assessed on 758 substrates using Biolog phenotype microarray technology. These data, along with available genomic sequences for all strains, were analyzed in light of rhizosphere colonization. Strains belonging to the P. chlororaphis subgroup colonized the rhizospheres of both plants more efficiently than strains belonging to the P. fluorescens subgroup. Metabolic results indicated that the ability to use amines and amino acids was associated with an increase in rhizosphere colonization capability in A. thaliana and/or in S. tuberosum The presence of multiple genetic determinants in the genomes of the different strains involved in catabolic pathways and plant-microbe and microbe-microbe interactions correlated with increased or decreased rhizosphere colonization capabilities in both plants. These results suggest that the metabolic and genomic traits found in different phenazine-producing Pseudomonas strains reflect their rhizosphere competence in A. thaliana and S. tuberosum Interestingly, most of these traits are associated with similar rhizosphere colonizing capabilities in both plant species.IMPORTANCE Rhizosphere colonization is crucial for plant growth promotion and biocontrol by antibiotic-producing Pseudomonas spp. This colonization process relies on different bacterial determinants which partly remain to be uncovered. In this study, we combined a metabolic and a genomic approach to decipher new rhizosphere colonization determinants which could improve our understanding of this process in Pseudomonas spp. Using 60 distinct strains of phenazine-producing Pseudomonas spp., we show that rhizosphere colonization abilities correlated with both metabolic and genomic traits when these bacteria were inoculated on two distant plants, Arabidopsis thaliana and Solanum tuberosum Key metabolic and genomic determinants presumably required for efficient colonization of both plant species were identified. Upon further validation, these targets could lead to the development of simple screening tests to rapidly identify efficient rhizosphere colonizers.

Cell morphology and nucleoid dynamics in dividing Deinococcus radiodurans.

Our knowledge of bacterial nucleoids originates mostly from studies of rod- or crescent-shaped bacteria. Here we reveal that Deinococcus radiodurans, a relatively large spherical bacterium with a multipartite genome, constitutes a valuable system for the study of the nucleoid in cocci. Using advanced microscopy, we show that D. radiodurans undergoes coordinated morphological changes at both the cellular and nucleoid level as it progresses through its cell cycle. The nucleoid is highly condensed, but also surprisingly dynamic, adopting multiple configurations and presenting an unusual arrangement in which oriC loci are radially distributed around clustered ter sites maintained at the cell centre. Single-particle tracking and fluorescence recovery after photobleaching studies of the histone-like HU protein suggest that its loose binding to DNA may contribute to this remarkable plasticity. These findings demonstrate that nucleoid organization is complex and tightly coupled to cell cycle progression in this organism.

Genome Mining Reveals Endopyrroles from a Nonribosomal Peptide Assembly Line Triggered in Fungal-Bacterial Symbiosis.

The bacterial endosymbiont (Burkholderia rhizoxinica) of the rice seedling blight fungus (Rhizopus microsporus) harbors a large number of cryptic biosynthesis gene clusters. Genome mining and sequence similarity networks based on an encoded nonribosomal peptide assembly line and the associated pyrrole-forming enzymes in the symbiont indicated that the encoded metabolites are unique among a large number of tentative pyrrole natural products in diverse and unrelated bacterial phyla. By performing comparative metabolic profiling using a mutant generated with an improved pheS Burkholderia counterselection marker, we found that the symbionts' biosynthetic pathway is mainly activated under salt stress and exclusively in symbiosis with the fungal host. The cryptic metabolites were fully characterized as novel pyrrole-substituted depsipeptides (endopyrroles). A broader survey showed that endopyrrole production is a hallmark of geographically distant endofungal bacteria, which produce the peptides solely under symbiotic conditions.

A century of gray: A genomic locus found in 2 distinct Pseudomonas spp. is associated with historical and contemporary color defects in dairy products worldwide.

Some gram-negative bacteria, including Pseudomonas spp., can grow at refrigeration temperatures and cause flavor, odor, and texture defects in fluid milk. Historical and modern cases exist of gray and blue color defects in fluid milk due to Pseudomonas, and several recent reports have detailed fresh cheese spoilage associated with blue-pigment-forming Pseudomonas. Our goal was to investigate the genomes of pigmented Pseudomonas isolates responsible for historical and modern pigmented spoilage of dairy products in the United States to determine the genetic basis of pigment-forming phenotypes. We performed whole genome sequencing of 9 Pseudomonas isolates: 3 from recent incidents of gray-pigmented fluid milk (Pseudomonas fluorescens group), 1 from blue-pigmented cheese (P. fluorescens group), 2 from a historical blue milk spoilage incident (Pseudomonas putida group), and 3 with no evidence for blue or gray pigment formation (2 from P. fluorescens group and 1 from Pseudomonas chlororaphis group). All 6 isolates collected from products with a gray or blue pigment defect were confirmed to produce pigment using potato dextrose agar or pasteurized milk. A subset of 2 isolates was selected for inoculation into milk and onto the surface of a model cheese for subsequent color measurement. These isolates produced different colors on potato dextrose agar, but produced nearly identical color defects in milk and on model cheese. For the same subset of 2 isolates, the gray color defect in milk was produced only in containers with ample headspace and not in full containers, suggesting that oxygen is vital for pigment formation. This work also demonstrated that a Pseudomonas isolate from cheese can produce a pigment defect in milk, and vice versa. Comparative genomics identified an accessory locus encoding tryptophan biosynthesis genes that was present in all isolates that produced gray or blue pigment under laboratory conditions and was only previously reported in 2 P. fluorescens isolates responsible for blue mozzarella in Italy. Because this locus was found in genetically distant isolates belonging to different Pseudomonas species groups, it may have been acquired via horizontal gene transfer. These data suggest that several past and present gray- or blue-pigmented dairy spoilage events share a common genetic etiology that transcends species-level identification and merits further investigation to determine mechanistic details and modes of prevention.

A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.

A genome-scale metabolic network reconstruction of Salinibacter ruber DSM13855 is presented here. To our knowledge, this is the first metabolic model of an organism in the phylum Rhodothermaeota. This model, which will be called iMB631, was reconstructed based on genomic and biochemical data available on the strain Salinibacter ruber DSM13855. This network consists of 1459 reactions, 1363 metabolites and 631 genes. Model evaluation was performed based on existing biochemical data in the literature and also by performing laboratory experiments. For growth on different carbon sources, we show that iMB631 is able to correctly predict the growth in 91% of cases where growth has been observed experimentally and 83% of conditions in which S. ruber did not grow. The F-score was 93%, demonstrating a generally acceptable performance of the model. Based on the predicted flux distributions, we found that under certain autotrophic condition, a reductive tricarboxylic acid cycle (rTCA) has fluxes in all necessary reactions to support autotrophic growth. To include special metabolites of the bacterium, salinixanthin biosynthesis pathway was modeled based on the pathway proposed recently. For years, main glucose consumption pathway has been under debates in S. ruber. Using flux balance analysis, iMB631 predicts pentose phosphate pathway, rather than glycolysis, as the active glucose consumption method in the S. ruber.

A Physiological and Genomic Comparison of Nitrosomonas Cluster 6a and 7 Ammonia-Oxidizing Bacteria.

Ammonia-oxidizing bacteria (AOB) within the genus Nitrosomonas perform the first step in nitrification, ammonia oxidation, and are found in diverse aquatic and terrestrial environments. Nitrosomonas AOB were grouped into six defined clusters, which correlate with physiological characteristics that contribute to adaptations to a variety of abiotic environmental factors. A fundamental physiological trait differentiating Nitrosomonas AOB is the adaptation to either low (cluster 6a) or high (cluster 7) ammonium concentrations. Here, we present physiological growth studies and genome analysis of Nitrosomonas cluster 6a and 7 AOB. Cluster 6a AOB displayed maximum growth rates at ≤ 1 mM ammonium, while cluster 7 AOB had maximum growth rates at ≥ 5 mM ammonium. In addition, cluster 7 AOB were more tolerant of high initial ammonium and nitrite concentrations than cluster 6a AOB. Cluster 6a AOB were completely inhibited by an initial nitrite concentration of 5 mM. Genomic comparisons were used to link genomic traits to observed physiological adaptations. Cluster 7 AOB encode a suite of genes related to nitrogen oxide detoxification and multiple terminal oxidases, which are absent in cluster 6a AOB. Cluster 6a AOB possess two distinct forms of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and select species encode genes for hydrogen or urea utilization. Several, but not all, cluster 6a AOB can utilize urea as a source of ammonium. Hence, although Nitrosomonas cluster 6a and 7 AOB have the capacity to fulfill the same functional role in microbial communities, i.e., ammonia oxidation, differentiating species-specific and cluster-conserved adaptations is crucial in understanding how AOB community succession can affect overall ecosystem function.

Chemical synthesis rewriting of a bacterial genome to achieve design flexibility and biological functionality.

Understanding how to program biological functions into artificial DNA sequences remains a key challenge in synthetic genomics. Here, we report the chemical synthesis and testing of Caulobacter ethensis-2.0 (C. eth-2.0), a rewritten bacterial genome composed of the most fundamental functions of a bacterial cell. We rebuilt the essential genome of Caulobacter crescentus through the process of chemical synthesis rewriting and studied the genetic information content at the level of its essential genes. Within the 785,701-bp genome, we used sequence rewriting to reduce the number of encoded genetic features from 6,290 to 799. Overall, we introduced 133,313 base substitutions, resulting in the rewriting of 123,562 codons. We tested the biological functionality of the genome design in C. crescentus by transposon mutagenesis. Our analysis revealed that 432 essential genes of C. eth-2.0, corresponding to 81.5% of the design, are equal in functionality to natural genes. These findings suggest that neither changing mRNA structure nor changing the codon context have significant influence on biological functionality of synthetic genomes. Discovery of 98 genes that lost their function identified essential genes with incorrect annotation, including a limited set of 27 genes where we uncovered noncoding control features embedded within protein-coding sequences. In sum, our results highlight the promise of chemical synthesis rewriting to decode fundamental genome functions and its utility toward the design of improved organisms for industrial purposes and health benefits.

Transcriptome and Comparative Genomics Analyses Reveal New Functional Insights on Key Determinants of Pathogenesis and Interbacterial Competition in Pectobacterium and Dickeya spp.

Soft-rot Enterobacteriaceae (SRE), typified by Pectobacterium and Dickeya genera, are phytopathogenic bacteria inflicting soft-rot disease in crops worldwide. By combining genomic information from 100 SRE with whole-transcriptome data sets, we identified novel genomic and transcriptional associations among key pathogenicity themes in this group. Comparative genomics revealed solid linkage between the type I secretion system (T1SS) and the carotovoricin bacteriophage (Ctv) conserved in 96.7% of Pectobacterium genomes. Moreover, their coactivation during infection indicates a novel functional association involving T1SS and Ctv. Another bacteriophage-borne genomic region, mostly confined to less than 10% of Pectobacterium strains, was found, presumably comprising a novel lineage-specific prophage in the genus. We also detected the transcriptional coregulation of a previously predicted toxin/immunity pair (WHH and SMI1_KNR4 families), along with the type VI secretion system (T6SS), which includes hcp and/or vgrG genes, suggesting a role in disease development as T6SS-dependent effectors. Further, we showed that another predicted T6SS-dependent endonuclease (AHH family) exhibited toxicity in ectopic expression assays, indicating antibacterial activity. Additionally, we report the striking conservation of the group 4 capsule (GFC) cluster in 100 SRE strains which consistently features adjacently conserved serotype-specific gene arrays comprising a previously unknown organization in GFC clusters. Also, extensive sequence variations found in gfcA orthologs suggest a serotype-specific role in the GfcABCD machinery.IMPORTANCE Despite the considerable loss inflicted on important crops yearly by Pectobacterium and Dickeya diseases, investigations on key virulence and interbacterial competition assets relying on extensive comparative genomics are still surprisingly lacking for these genera. Such approaches become more powerful over time, underpinned by the growing amount of genomic information in public databases. In particular, our findings point to new functional associations among well-known genomic themes enabling alternative means of neutralizing SRE diseases through disruption of pivotal virulence programs. By elucidating novel transcriptional and genomic associations, this study adds valuable information on virulence candidates that could be decisive in molecular applications in the near future. The utilization of 100 genomes of Pectobacterium and Dickeya strains in this study is unprecedented for comparative analyses in these taxa, and it provides novel insights on the biology of economically important plant pathogens.

A k-mer-based method for the identification of phenotype-associated genomic biomarkers and predicting phenotypes of sequenced bacteria.

We have developed an easy-to-use and memory-efficient method called PhenotypeSeeker that (a) identifies phenotype-specific k-mers, (b) generates a k-mer-based statistical model for predicting a given phenotype and (c) predicts the phenotype from the sequencing data of a given bacterial isolate. The method was validated on 167 Klebsiella pneumoniae isolates (virulence), 200 Pseudomonas aeruginosa isolates (ciprofloxacin resistance) and 459 Clostridium difficile isolates (azithromycin resistance). The phenotype prediction models trained from these datasets obtained the F1-measure of 0.88 on the K. pneumoniae test set, 0.88 on the P. aeruginosa test set and 0.97 on the C. difficile test set. The F1-measures were the same for assembled sequences and raw sequencing data; however, building the model from assembled genomes is significantly faster. On these datasets, the model building on a mid-range Linux server takes approximately 3 to 5 hours per phenotype if assembled genomes are used and 10 hours per phenotype if raw sequencing data are used. The phenotype prediction from assembled genomes takes less than one second per isolate. Thus, PhenotypeSeeker should be well-suited for predicting phenotypes from large sequencing datasets. PhenotypeSeeker is implemented in Python programming language, is open-source software and is available at GitHub (https://github.com/bioinfo-ut/PhenotypeSeeker/).

Genome-scale analysis of Acetobacterium bakii reveals the cold adaptation of psychrotolerant acetogens by post-transcriptional regulation.

Acetogens synthesize acetyl-CoA via CO2 or CO fixation, producing organic compounds. Despite their ecological and industrial importance, their transcriptional and post-transcriptional regulation has not been systematically studied. With completion of the genome sequence of Acetobacterium bakii (4.28-Mb), we measured changes in the transcriptome of this psychrotolerant acetogen in response to temperature variations under autotrophic and heterotrophic growth conditions. Unexpectedly, acetogenesis genes were highly up-regulated at low temperatures under heterotrophic, as well as autotrophic, growth conditions. To mechanistically understand the transcriptional regulation of acetogenesis genes via changes in RNA secondary structures of 5'-untranslated regions (5'-UTR), the primary transcriptome was experimentally determined, and 1379 transcription start sites (TSS) and 1100 5'-UTR were found. Interestingly, acetogenesis genes contained longer 5'-UTR with lower RNA-folding free energy than other genes, revealing that the 5'-UTRs control the RNA abundance of the acetogenesis genes under low temperature conditions. Our findings suggest that post-transcriptional regulation via RNA conformational changes of 5'-UTRs is necessary for cold-adaptive acetogenesis.