ICEberg 3.0: functional categorization and analysis of the integrative and conjugative elements in bacteria.

ICEberg 3.0 (https://tool2-mml.sjtu.edu.cn/ICEberg3/) is an upgraded database that provides comprehensive insights into bacterial integrative and conjugative elements (ICEs). In comparison to the previous version, three key enhancements were introduced: First, through text mining and manual curation, it now encompasses details of 2065 ICEs, 607 IMEs and 275 CIMEs, including 430 with experimental support. Secondly, ICEberg 3.0 systematically categorizes cargo gene functions of ICEs into six groups based on literature curation and predictive analysis, providing a profound understanding of ICEs'diverse biological traits. The cargo gene prediction pipeline is integrated into the online tool ICEfinder 2.0. Finally, ICEberg 3.0 aids the analysis and exploration of ICEs from the human microbiome. Extracted and manually curated from 2405 distinct human microbiome samples, the database comprises 1386 putative ICEs, offering insights into the complex dynamics of Bacteria-ICE-Cargo networks within the human microbiome. With the recent updates, ICEberg 3.0 enhances its capability to unravel the intricacies of ICE biology, particularly in the characterization and understanding of cargo gene functions and ICE interactions within the microbiome. This enhancement may facilitate the investigation of the dynamic landscape of ICE biology and its implications for microbial communities.

oriTDB: a database of the origin-of-transfer regions of bacterial mobile genetic elements.

Conjugation and mobilization are two important pathways of horizontal transfer of bacterial mobile genetic elements (MGEs). The origin-of-transfer (oriT) region is crucial for this process, serving as a recognition site for relaxase and containing the DNA nicking site (nic site), which initiates the conjugation or mobilization. Here, we present a database of the origin-of-transfer regions of bacterial MGEs, oriTDB (https://bioinfo-mml.sjtu.edu.cn/oriTDB2/). Incorporating data from text mining and genome analysis, oriTDB comprises 122 experimentally validated and 22 927 predicted oriTs within bacterial plasmids, Integrative and Conjugative Elements, and Integrative and Mobilizable Elements. Additionally, oriTDB includes details about associated relaxases, auxiliary proteins, type IV coupling proteins, and a gene cluster encoding the type IV secretion system. The database also provides predicted secondary structures of oriT sequences, dissects oriT regions into pairs of inverted repeats, nic sites, and their flanking conserved sequences, and offers an interactive visual representation. Furthermore, oriTDB includes an enhanced oriT prediction pipeline, oriTfinder2, which integrates a functional annotation module for cargo genes in bacterial MGEs. This resource is intended to support research on bacterial conjugative or mobilizable elements and promote an understanding of their cargo gene functions.

TADB 3.0: an updated database of bacterial toxin-antitoxin loci and associated mobile genetic elements.

TADB 3.0 (https://bioinfo-mml.sjtu.edu.cn/TADB3/) is an updated database that provides comprehensive information on bacterial types I to VIII toxin-antitoxin (TA) loci. Compared with the previous version, three major improvements are introduced: First, with the aid of text mining and manual curation, it records the details of 536 TA loci with experimental support, including 102, 403, 8, 14, 1, 1, 3 and 4 TA loci of types I to VIII, respectively; Second, by leveraging the upgraded TA prediction tool TAfinder 2.0 with a stringent strategy, TADB 3.0 collects 211 697 putative types I to VIII TA loci predicted in 34 789 completely sequenced prokaryotic genomes, providing researchers with a large-scale dataset for further follow-up analysis and characterization; Third, based on their genomic locations, relationships of 69 019 TA loci and 60 898 mobile genetic elements (MGEs) are visualized by interactive networks accessible through the user-friendly web page. With the recent updates, TADB 3.0 may provide improved in silico support for comprehending the biological roles of TA pairs in prokaryotes and their functional associations with MGEs.

Transposition with Tn3-family elements occurs through interaction with the host ß-sliding clamp processivity factor.

Tn3 family transposons are a widespread group of replicative transposons, notorious for contributing to the dissemination of antibiotic resistance, particularly the global prevalence of carbapenem resistance. The transposase (TnpA) of these elements catalyzes DNA breakage and rejoining reactions required for transposition. However, the molecular mechanism for target site selection with these elements remains unclear. Here, we identify a QLxxLR motif in N-terminal of Tn3 TnpAs and demonstrate that this motif allows interaction between TnpA of Tn3 family transposon Tn1721 and the host ß-sliding clamp (DnaN), the major processivity factor of the DNA replication machinery. The TnpA-DnaN interaction is essential for Tn1721 transposition. Our work unveils a mechanism whereby Tn3 family transposons can bias transposition into certain replisomes through an interaction with the host replication machinery. This study further expands the diversity of mobile elements that use interaction with the host replication machinery to bias integration.

T4SEfinder: a bioinformatics tool for genome-scale prediction of bacterial type IV secreted effectors using pre-trained protein language model.

Bacterial type IV secretion systems (T4SSs) are versatile and membrane-spanning apparatuses, which mediate both genetic exchange and delivery of effector proteins to target eukaryotic cells. The secreted effectors (T4SEs) can affect gene expression and signal transduction of the host cells. As such, they often function as virulence factors and play an important role in bacterial pathogenesis. Nowadays, T4SE prediction tools have utilized various machine learning algorithms, but the accuracy and speed of these tools remain to be improved. In this study, we apply a sequence embedding strategy from a pre-trained language model of protein sequences (TAPE) to the classification task of T4SEs. The training dataset is mainly derived from our updated type IV secretion system database SecReT4 with newly experimentally verified T4SEs. An online web server termed T4SEfinder is developed using TAPE and a multi-layer perceptron (MLP) for T4SE prediction after a comprehensive performance comparison with several candidate models, which achieves a slightly higher level of accuracy than the existing prediction tools. It only takes about 3 minutes to make a classification for 5000 protein sequences by T4SEfinder so that the computational speed is qualified for whole genome-scale T4SEs detection in pathogenic bacteria. T4SEfinder might contribute to meet the increasing demands of re-annotating secretion systems and effector proteins in sequenced bacterial genomes. T4SEfinder is freely accessible at https://tool2-mml.sjtu.edu.cn/T4SEfinder_TAPE/.

High prevalence of polymyxin-heteroresistant carbapenem-resistant Klebsiella pneumoniae and its within-host evolution to resistance among critically ill scenarios.

PURPOSE: We aimed to explore the prevalence and within-host evolution of resistance in polymyxin-heteroresistant carbapenem-resistant Klebsiella pneumoniae (PHR-CRKP) in critically ill patients. METHODS: We performed an epidemiological analysis of consecutive patients with PHR-CRKP from clinical cases. Our study investigated the within-host resistance evolution and its clinical significance during polymyxin exposure. Furthermore, we explored the mechanisms underlying the dynamic evolution of polymyxin resistance at both subpopulation and genetic levels, involved population analysis profile test, time-killing assays, competition experiments, and sanger sequencing. Additionally, comparative genomic analysis was performed on 713 carbapenemase-producing K. pneumoniae strains. RESULTS: We enrolled 109 consecutive patients, and PHR-CRKP was found in 69.7% of patients without previous polymyxin exposure. 38.1% of PHR-CRKP isolates exhibited polymyxin resistance and led to therapeutic failure in critically ill scenarios. An increased frequency of resistant subpopulations was detected during PHR-CRKP evolution, with rapid regrowth of resistant subpopulations under high polymyxin concentrations, and a fitness cost in an antibiotic-free environment. Mechanistic analysis revealed that diverse mgrB insertions and pmrB hypermutations contributed to the dynamic changes in polymyxin susceptibility in dominant resistant subpopulations during PHR evolution, which were validated by comparative genomic analysis. Several deleterious mutations (e.g. pmrBLeu82Arg, pmrBSer85Arg) were firstly detected during PHR-CRKP evolution. Indeed, specific sequence types of K. pneumoniae demonstrated unique deletions and deleterious mutations. CONCLUSIONS: Our study emphasizes the high prevalence of pre-existing heteroresistance in CRKP, which can lead to polymyxin resistance and fatal outcomes. Hence, it is essential to continuously monitor and observe the treatment response to polymyxins in appropriate critically ill scenarios.

VRprofile2: detection of antibiotic resistance-associated mobilome in bacterial pathogens.

VRprofile2 is an updated pipeline that rapidly identifies diverse mobile genetic elements in bacterial genome sequences. Compared with the previous version, three major improvements were made. First, the user-friendly visualization could aid users in investigating the antibiotic resistance gene cassettes in conjunction with various mobile elements in the multiple resistance region with mosaic structure. VRprofile2 could compare the predicted mobile elements to the collected known mobile elements with similar architecture. A new mobilome indicator was proposed to give an overall estimation of the mobilome size in individual bacterial genomes. Second, the relationship between antibiotic resistance genes, mobile elements, and host strains would be efficiently examined with the aid of predicted strain's sequence typing, the incompatibility group and the transferability of plasmids. Finally, the updated back-end database, MobilomeDB2, now collected nearly a thousand active mobile elements retrieved from literature or based on prediction. The pre-computed results of the antibiotic resistance gene-carrying mobile elements of >5500 ESKAPEE genomes were also provided. We expect that VRprofile2 will provide better support for researchers interested in bacterial mobile elements and the dissemination of antibiotic resistance. VRprofile2 is freely available to all users without any login requirement at https://tool2-mml.sjtu.edu.cn/VRprofile.

Antibiotic-induced degradation of antitoxin enhances the transcription of acetyltransferase-type toxin-antitoxin operon.

BACKGROUND: Bacterial toxin-antitoxin (TA) modules respond to various stressful conditions. The Gcn5-related N-acetyltransferase-type toxin (GNAT) protein encoded by the GNAT-RHH TA locus is involved in the antibiotic tolerance of Klebsiella pneumoniae. OBJECTIVES: To investigate the transcriptional mechanism of the GNAT-RHH operon kacAT under antibiotic stress. METHODS: The transcriptional level of the kacAT operon of K. pneumoniae was measured by quantitative real-time (qRT) PCR assay. The degradation of antitoxin KacA was examined by western blot and fluorescent protein. The ratio of [KacA]:[KacT] was calculated by the fluorescence intensity of KacA-eGFP and mCherry-KacT. Mathematical modelling predicted protein and transcript synthesis dynamics. RESULTS: A meropenem-induced increase in transcript levels of kacA and kacT resulted from the relief from transcriptional autoregulation of the kacAT operon. Meropenem induces the degradation of KacA through Lon protease, resulting in a reduction in the ratio of [KacA]:[KacT]. The decreased ratio causes the dissociation of the KacAT complex from its promoter region, which eliminates the repression of kacAT transcription. In addition, our dynamic model of kacAT expression regulation quantitatively reproduced the experimentally observed reduction of the [KacA]:[KacT] ratio and a large increase in kacAT transcript levels under the condition of strong promoter autorepression by the KacAT complex. CONCLUSIONS: Meropenem promotes the degradation of antitoxin by enhancing the expression of Lon protease. Degradation of antitoxin reduces the ratio of intracellular [antitoxin]:[toxin], leading to detachment of the TA complex from its promoter, and releasing repression of TA operon transcription. These results may provide an important insight into the transcriptional mechanism of GNAT-RHH TA modules under antibiotic stress.

ICEberg 2.0: an updated database of bacterial integrative and conjugative elements.

ICEberg 2.0 (http://db-mml.sjtu.edu.cn/ICEberg/) is an updated database that provides comprehensive information about bacterial integrative and conjugative elements (ICEs). Compared with the previous version, three major improvements were made. First, with the aid of text mining and manual curation, it now recorded the details of 1032 ICEs, including 270 with experimental supports and 762 from bioinformatics prediction. Second, as increasing evidence has shown that ICEs frequently mobilize the so-called 'hitchhikers', such as integrative and mobilizable elements (IMEs) and cis-mobilizable elements (CIMEs), 83 known transfer interactions between 49 IMEs and 7 CIMEs with 19 ICEs taken from the literature were included and illustrated with visually intuitive directed graphs. An expanded collection of 260 chromosome-borne IMEs and 235 CIMEs was also added. At last, ICEberg 2.0 provides an online tool ICEfinder to predict ICEs or IMEs in bacterial genome sequences. It combines a similarity search for the integrase, relaxase and/or type IV secretion system and the co-localization of these corresponding homologous genes. With the recent updates, ICEberg 2.0 might provide better support for understanding the biological traits of ICEs, especially as their interaction with cognate mobilizable elements may further promote horizontal gene flow.

Toxin-antitoxin operon kacAT of Klebsiella pneumoniae is regulated by conditional cooperativity via a W-shaped KacA-KacT complex.

Bacterial toxin-antitoxin pairs play important roles in bacterial multidrug tolerance. Gcn5-related N-acetyltransferase (GNAT) toxins inhibit translation by acetylation of aminoacyl-tRNAs and are counteracted by direct contacts with cognate ribbon-helix-helix (RHH) antitoxins. Our previous analysis showed that the GNAT toxin KacT and RHH antitoxin KacA of Klebsiella pneumoniae form a heterohexamer in solution and that the complex interacts with the cognate promoter DNA, resulting in negative autoregulation of kacAT transcription. Here, we present the crystal structure of DNA-bound KacAT complex at 2.2 Å resolution. The crystal structure revealed the formation of a unique heterohexamer, KacT-KacA2-KacA2-KacT. The direct interaction of KacA and KacT involves a unique W-shaped structure with the two KacT molecules at opposite ends. Inhibition of KacT is achieved by the binding of four KacA proteins that preclude the formation of an active KacT dimer. The kacAT operon is auto-regulated and we present an experimentally supported molecular model proposing that the KacT:KacA ratio controls kacAT transcription by conditional cooperativity. These results yield a profound understanding of how transcription GNAT-RHH pairs are regulated.

Absence of the type I-E CRISPR-Cas system in Klebsiella pneumoniae clonal complex 258 is associated with dissemination of IncF epidemic resistance plasmids in this clonal complex.

BACKGROUND: The pandemics caused by MDR Klebsiella pneumoniae are mostly due to the global dissemination of high-risk clonal complex 258 (CC258) and related IncF epidemic plasmids. However, the factors leading to the epidemiological advantages of CC258-IncF linkage remain obscure. The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) and CRISPR-associated protein (CRISPR-Cas) systems, providing adaptive immunity against invading DNA, play an important role in the interactions between plasmids and hosts. OBJECTIVES: To investigate the relationship between CRISPR-Cas systems and the high-risk linkage CC258-IncF. METHODS: CRISPR-Cas loci were detected among 381 collected K. pneumoniae clinical isolates and 207 K. pneumoniae complete genomes available in GenBank. MLST was used to determine the genetic relatedness of these isolates. Nucleotide BLAST was used to search for protospacers on K. pneumoniae plasmids. RESULTS: We observed an epidemic correlation between CRISPR-Cas loci, CC258 and IncF plasmids. Interestingly, most type I-E CRISPR-Cas systems identified carried spacers matching the backbone regions of IncF plasmids. CONCLUSIONS: Our results suggest that the absence of type I-E CRISPR-Cas systems in K. pneumoniae CC258 is strongly associated with the dissemination of IncF epidemic plasmids, contributing to the global success of the international high-risk linkage CC258-IncF. Our findings provide new information regarding the dissemination and evolution of the high-risk linkage of K. pneumoniae CC258-IncF and pave the way for new strategies to address the problem of antibiotic resistance.

VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria.

VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile.

oriTfinder: a web-based tool for the identification of origin of transfers in DNA sequences of bacterial mobile genetic elements.

oriTfinder is a web server that facilitates the rapid identification of the origin of transfer site (oriT) of a conjugative plasmid or chromosome-borne integrative and conjugative element. The utilized back-end database oriTDB was built upon more than one thousand known oriT regions of bacterial mobile genetic elements (MGEs) as well as the known MGE-encoding relaxases and type IV coupling proteins (T4CP). With a combination of similarity searches for the oriTDB-archived oriT nucleotide sequences and the co-localization of the flanking relaxase homologous genes, the oriTfinder can predict the oriT region with high accuracy in the DNA sequence of a bacterial plasmid or chromosome in minutes. The server also detects the other transfer-related modules, including the potential relaxase gene, T4CP gene and the type IV secretion system gene cluster, and the putative genes coding for virulence factors and acquired antibiotic resistance determinants. oriTfinder may contribute to meeting the increasing demands of re-annotations for bacterial conjugative, mobilizable or non-transferable elements and aid in the rapid risk accession of disease-relevant trait dissemination in pathogenic bacteria of interest. oriTfinder is freely available to all users without any login requirement at http://bioinfo-mml.sjtu.edu.cn/oriTfinder.

TADB 2.0: an updated database of bacterial type II toxin-antitoxin loci.

TADB2.0 (http://bioinfo-mml.sjtu.edu.cn/TADB2/) is an updated database that provides comprehensive information about bacterial type II toxin-antitoxin (TA) loci. Compared with the previous version, the database refined and the new data schema is employed. With the aid of text mining and manual curation, it recorded 6193 type II TA loci in 870 replicons of bacteria and archaea, including 105 experimentally validated TA loci. In addition, the newly developed tool TAfinder combines the homolog searches and the operon structure detection, allowing the prediction for type II TA pairs in bacterial genome sequences. It also helps to investigate the genomic context of predicted TA loci for putative virulence factors, antimicrobial resistance determinants and mobile genetic elements via alignments to the specific public databases. Additionally, the module TAfinder-Compare allows comparing the presence of the given TA loci across the close relative genomes. With the recent updates, TADB2.0 might provide better support for understanding the important roles of type II TA systems in the prokaryotic life activities.

Identification and characterization of acetyltransferase-type toxin-antitoxin locus in Klebsiella pneumoniae.

A type II toxin-antitoxin (TA) system, in which the toxin contains a Gcn5-related N-acetyltransferase (GNAT) domain, has been characterized recently. GNAT toxin acetylates aminoacyl-tRNA and blocks protein translation. It is abolished by the cognate antitoxin that contains the ribbon-helix-helix (RHH) domain. Here, we present an experimental demonstration of the interaction of the GNAT-RHH complex with TA promoter DNA. First, the GNAT-RHH TA locus kacAT was found in Klebsiella pneumoniae HS11286, a strain resistant to multiple antibiotics. Overexpression of KacT halted cell growth and resulted in persister cell formation. The crystal structure also indicated that KacT is a typical acetyltransferase toxin. Co-expression of KacA neutralized KacT toxicity. Expression of the bicistronic kacAT locus was up-regulated during antibiotic stress. Finally, KacT and KacA formed a heterohexamer that interacted with promoter DNA, resulting in negative autoregulation of kacAT transcription. The N-terminus region of KacA accounted for specific binding to the palindromic sequence on the operator DNA, whereas its C-terminus region was essential for the inactivation of the GNAT toxin. These results provide an important insight into the regulation of the GNAT-RHH family TA system.

Large-Scale Identification of AbaR-Type Genomic Islands in Acinetobacter baumannii Reveals Diverse Insertion Sites and Clonal Lineage-Specific Antimicrobial Resistance Gene Profiles.

AbaR-type genomic islands (AbaRs) are important elements responsible for antimicrobial resistance in Acinetobacter baumannii This study performed a large-scale identification of AbaRs to understand their distribution and compositions of antimicrobial resistance genes. We identified 2.89-kb left-end and 1.87-kb right-end conserved sequences (CSs) and developed a bioinformatics approach to identify AbaRs, using the CSs as signatures, in 3,148 publicly available genomes. AbaRs were prevalent in A. baumannii, being found in 2,091 genomes. They were sparse in other Acinetobacter species and confined only to this genus. Results from 111 complete genomes showed that over 85% of AbaRs resided on chromosomes. The external flanks adjacent to the inverted repeats available in all identified CSs were mapped to an AbaR-free chromosome or searched in the NCBI database for empty loci to define insertion sites. Surprisingly, 84 insertion sites with diverse origins were revealed, including 51 scattered on the chromosome, 20 plasmid borne, 12 located on prophages, transposons, ISAba1, complex AbaRs, and genomic islands of other types, and one uncharacterized, and some were strongly associated with clonal lineages. Finally, we found 994 antimicrobial resistance genes covering 28 unique genes from 70.9% (299/422) of intact AbaRs currently available. The resistance gene profiles displayed an apparent clonal lineage-specific pattern, highlighting the distinct features of AbaRs in global clone 1 (GC1) and GC2. The tet(B) gene was highly specific to the AbaRs in GC2. In conclusion, AbaRs have diverse insertion sites on the chromosome and mobile genetic elements (MGEs) and display distinct antimicrobial resistance gene profiles in different clonal lineages.

Type VI secretion system contributes to Enterohemorrhagic Escherichia coli virulence by secreting catalase against host reactive oxygen species (ROS).

Enterohemorrhagic Escherichia coli (EHEC) is one major type of contagious and foodborne pathogens. The type VI secretion system (T6SS) has been shown to be involved in the bacterial pathogenicity and bacteria-bacteria competition. Here, we show that EHEC could secrete a novel effector KatN, a Mn-containing catalase, in a T6SS-dependent manner. Expression of katN is promoted by RpoS and OxyR and repressed by H-NS, and katN contributes to bacterial growth under oxidative stress in vitro. KatN could be secreted into host cell cytosol after EHEC is phagocytized by macrophage, which leads to decreased level of intracellular reactive oxygen species (ROS) and facilitates the intramacrophage survival of EHEC. Finally, animal model results show that the deletion mutant of T6SS was attenuated in virulence compared with the wild type strain, while the deletion mutant of katN had comparable virulence to the wild type strain. Taken together, our findings suggest that EHEC could sense oxidative stress in phagosome and decrease the host cell ROS by secreting catalase KatN to facilitate its survival in the host cells.

In Silico Typing and Comparative Genomic Analysis of IncFIIK Plasmids and Insights into the Evolution of Replicons, Plasmid Backbones, and Resistance Determinant Profiles.

IncFIIK plasmids are associated with the acquisition and dissemination of multiple-antimicrobial resistance in Klebsiella pneumoniae and often encountered in clinical isolates of this species. Since the phylogeny and evolution of IncFIIK plasmids remain unclear, here we performed large-scale in silico typing and comparative analysis of these plasmids in publicly available bacterial/plasmid genomes. IncFIIK plasmids are prevalent in K. pneumoniae, being found in 69% of sequenced genomes, covering 66% of sequenced STs (sequence types), but sparse in other Enterobacteriaceae IncFIIK replicons have three lineages. One IncFIIK allele could be found in distinct K. pneumoniae STs, highlighting the lateral genetic flow of IncFIIK plasmids. A set of 77 IncFIIK plasmids with full sequences were further analyzed. A pool of 327 antibiotic resistance genes or remnants were annotated in 75.3% of these plasmids. Plasmid genome comparison reiterated that they often contain other replicons belonging to IncFIA, IncFIB, IncFIIYp, IncFIIpCRY, IncR, IncL, and IncN groups and that they share a conserved backbone featuring an F-like conjugation module that has divergent components responsible for regulation and mating pair stabilization. Further epidemiological studies of IncFIIK plasmids are required due to the sample bias of K. pneumoniae genomes in public databases. This study provides insights into the evolution and structures of IncFIIK plasmids.

Large-Scale Transposition Mutagenesis of Streptomyces coelicolor Identifies Hundreds of Genes Influencing Antibiotic Biosynthesis.

Gram-positive Streptomyces bacteria produce thousands of bioactive secondary metabolites, including antibiotics. To systematically investigate genes affecting secondary metabolism, we developed a hyperactive transposase-based Tn5 transposition system and employed it to mutagenize the model species Streptomyces coelicolor, leading to the identification of 51,443 transposition insertions. These insertions were distributed randomly along the chromosome except for some preferred regions associated with relatively low GC content in the chromosomal core. The base composition of the insertion site and its flanking sequences compiled from the 51,443 insertions implied a 19-bp expanded target site surrounding the insertion site, with a slight nucleic acid base preference in some positions, suggesting a relative randomness of Tn5 transposition targeting in the high-GC Streptomyces genome. From the mutagenesis library, 724 mutants involving 365 genes had altered levels of production of the tripyrrole antibiotic undecylprodigiosin (RED), including 17 genes in the RED biosynthetic gene cluster. Genetic complementation revealed that most of the insertions (more than two-thirds) were responsible for the changed antibiotic production. Genes associated with branched-chain amino acid biosynthesis, DNA metabolism, and protein modification affected RED production, and genes involved in signaling, stress, and transcriptional regulation were overrepresented. Some insertions caused dramatic changes in RED production, identifying future targets for strain improvement.IMPORTANCE High-GC Gram-positive streptomycetes and related actinomycetes have provided more than 100 clinical drugs used as antibiotics, immunosuppressants, and antitumor drugs. Their genomes harbor biosynthetic genes for many more unknown compounds with potential as future drugs. Here we developed a useful genome-wide mutagenesis tool based on the transposon Tn5 for the study of secondary metabolism and its regulation. Using Streptomyces coelicolor as a model strain, we found that chromosomal insertion was relatively random, except at some hot spots, though there was evidence of a slightly preferred 19-bp target site. We then used prodiginine production as a model to systematically survey genes affecting antibiotic biosynthesis, providing a global view of antibiotic regulation. The analysis revealed 348 genes that modulate antibiotic production, among which more than half act to reduce production. These might be valuable targets in future investigations of regulatory mechanisms, for strain improvement, and for the activation of silent biosynthetic gene clusters.

PDC-SGB: Prediction of effective drug combinations using a stochastic gradient boosting algorithm.

Combinatorial therapy is a promising strategy for combating complex diseases by improving the efficacy and reducing the side effects. To facilitate the identification of drug combinations in pharmacology, we proposed a new computational model, termed PDC-SGB, to predict effective drug combinations by integrating biological, chemical and pharmacological information based on a stochastic gradient boosting algorithm. To begin with, a set of 352 golden positive samples were collected from the public drug combination database. Then, a set of 732 dimensional feature vector involving biological, chemical and pharmaceutical information was constructed for each drug combination to describe its properties. To avoid overfitting, the maximum relevance & minimum redundancy (mRMR) method was performed to extract useful ones by removing redundant subsets. Based on the selected features, the three different type of classification algorithms were employed to build the drug combination prediction models. Our results demonstrated that the model based on the stochastic gradient boosting algorithm yield out the best performance. Furthermore, it is indicated that the feature patterns of therapy had powerful ability to discriminate effective drug combinations from non-effective ones. By analyzing various features, it is shown that the enriched features occurred frequently in golden positive samples can help predict novel drug combinations.