Liposomal Encapsulation Increases the Efficacy of Azithromycin against Chlamydia trachomatis

Chlamydia trachomatis (C. trachomatis) is an obligate intracellular bacterium linked to ocular and urogenital infections with potentially serious sequelae, including blindness and infertility. First-line antibiotics, such as azithromycin (AZT) and doxycycline, are effective, but treatment failures have also been reported. Encapsulation of antibiotics in liposomes is considered an effective approach for improving their local effects, bioavailability, biocompatibility and antimicrobial activity. To test whether liposomes could enhance the antichlamydial action of AZT, we encapsulated AZT in different surface-charged elastic liposomes (neutral, cationic and anionic elastic liposomes) and assessed their antibacterial potential against the C. trachomatis serovar D laboratory strain as well as the clinical isolate C. trachomatis serovar F. A direct quantitative polymerase chain reaction (qPCR) method was used to measure chlamydial genome content 48 h post infection and to determine the recoverable chlamydial growth. All the liposomes efficiently delivered AZT to HeLa 229 cells infected with the laboratory Chlamydia strain, exhibiting the minimal inhibitory concentrations (MIC) and the minimal bactericidal concentrations (MBC) of AZT even 4–8-fold lower than those achieved with the free AZT. The tested AZT-liposomes were also effective against the clinical Chlamydia strain by decreasing MIC values by 2-fold relative to the free AZT. Interestingly, the neutral AZT-liposomes had no effect on the MBC against the clinical strain, while cationic and anionic AZT-liposomes decreased the MBC 2-fold, hence proving the potential of the surface-charged elastic liposomes to improve the effectiveness of AZT against C. trachomatis.

Machine learning approaches to predict the Plant-associated phenotype of Xanthomonas strains

Background The genus Xanthomonas has long been considered to consist predominantly of plant pathogens, but over the last decade there has been an increasing number of reports on non-pathogenic and endophytic members. As Xanthomonas species are prevalent pathogens on a wide variety of important crops around the world, there is a need to distinguish between these plant-associated phenotypes. To date a large number of Xanthomonas genomes have been sequenced, which enables the application of machine learning (ML) approaches on the genome content to predict this phenotype. Until now such approaches to the pathogenomics of Xanthomonas strains have been hampered by the fragmentation of information regarding pathogenicity of individual strains over many studies. Unification of this information into a single resource was therefore considered to be an essential step. Results Mining of 39 papers considering both plant-associated phenotypes, allowed for a phenotypic classification of 578 Xanthomonas strains. For 65 plant-pathogenic and 53 non-pathogenic strains the corresponding genomes were available and de novo annotated for the presence of Pfam protein domains used as features to train and compare three ML classification algorithms; CART, Lasso and Random Forest. Conclusion The literature resource in combination with recursive feature extraction used in the ML classification algorithms provided further insights into the virulence enabling factors, but also highlighted domains linked to traits not present in pathogenic strains.

Genome Survey Sequencing of an Iconic ‘Trophy’ Sportfish, the Roosterfish Nematistius pectoralis: Genome Size, Repetitive Elements, Nuclear RNA Gene Operon, and Microsatellite Discovery

The ‘Pez Gallo’ or the Roosterfish, Nematistius pectoralis, is an ecologically relevant species in the shallow water soft-bottom environments and a target of a most lucrative recreational sport fishery in the Central Eastern Pacific Ocean. According to the International Union for Conservation of Nature, N. pectoralis is assessed globally as Data Deficient. Using low-coverage short Illumina 300 bp pair-end reads sequencing, this study reports, for the first time, the genome size, single/low-copy genome content, and nuclear repetitive elements, including the 45S rRNA DNA operon and microsatellites, in N. pectoralis. The haploid genome size estimated using a k-mer approach was 816.04 Mbp, which is within the range previously reported for other representatives of the Carangiformes order. Single/low-copy genome content (63%) was relatively high. A large portion of repetitive sequences could not be assigned to the known repeat element families. Considering only annotated repetitive elements, the most common were classified as Satellite DNA which were considerably more abundant than Class I-Long Interspersed Nuclear Elements and Class I-LTR Retroviral elements. The nuclear ribosomal operon in N. pectoralis consists of, in the following order: a 5′ ETS (length = 948 bp), ssrDNA (1835 bp), ITS1 (724 bp), a 5.8S rDNA (158 bp), ITS2 (508 bp), lsrDNA (3924 bp), and a 3′ ETS (32 bp). A total of 44 SSRs were identified. These newly developed genomic resources are most relevant for improving the understanding of biology, developing conservation plans, and managing the fishery of the iconic N. pectoralis.

iLoci: Robust evaluation of genome content and organization for provisional and mature genome assemblies

Background: The rate at which new draft genome assemblies and corresponding annotation versions are being produced has long outpaced the scientific community's capacity to refine these drafts into finished, reference-quality data resources to a standard typically expected from dedicated efforts of model organism research communities. Nonetheless, scientists must be able to evaluate newly sequenced genomes in the context of previously published data, requiring summaries of genome content and organization that can be quickly computed, updated, and meaningfully compared. As annotation quality will necessarily vary within and across data sets, the ability to select subsets of only those data that are well supported is critical for distinguishing technical artifacts from biological effects in genome-wide analyses. Results: We introduce a new framework for genome analyses based on parsing an annotated genome assembly into distinct interval loci (iLoci), available as open source software as part of the AEGeAn Toolkit (https://github.com/BrendelGroup/AEGeAn). We demonstrate that iLoci provide an alternative coordinate system that is robust to changes in assembly and annotation versions and facilitates granular quality control of genome data. We discuss how statistics computed on iLoci reflect various characteristics of genome content and organization and illustrate how these statistics can be used to establish a baseline for assessment of the completeness and accuracy of the data. We also introduce a well-defined measure of relative genome compactness and compute other iLocus statistics that reveal genome-wide characteristics of gene arrangements in the whole genome context. Conclusions: We present a coherent computational framework that calculates informative statistics from genome assembly/annotation data input. Given the fast pace of assembly/annotation updates, our AEGeAn Toolkit fills a niche in computational genomics based on deriving persistent and species-specific genome statistics. Gene structure model centric iLoci provide a precisely defined coordinate system that can be used to store assembly/annotation updates that reflect either stable or changed assessments. Large-scale application of the approach revealed species and clade specific genome organization in precisely defined computational terms, promising intriguing forays into the forces of shaping genome structure as more and more genome assemblies are being deposited.

The evolutionary origin of host association in an ancient bacterial clade

The evolution of obligate host-association of bacterial symbionts and pathogens remains poorly understood. The Rickettsiales represent an order of obligate alphaproteobacterial endosymbionts and parasites that infect a wide variety of eukaryotic hosts, including humans, livestock, insects and protists. Induced by their host-associated lifestyle, Rickettsiales genomes have undergone reductive evolution, leading to small, AT-rich genomes with limited metabolic capacities. We describe several genomes of deep-branching, environmental alphaproteobacteria that branch basal to previously sampled Rickettsiales, and whose genome content are reminiscent of free-living and biofilm-associated lifestyles. Ancestral genome content reconstruction across the Rickettsiales tree revealed that the free-living to host-association transition of this group occurred more recently than previously anticipated, and likely involved the repurposing of a type IV secretion system.One-Sentence SummaryDeep-branching Rickettsiales provide insights into the evolution of obligate host-associated lifestyle

Transcription coordinates histone amounts and genome content

Biochemical reactions typically depend on the concentrations of the molecules involved, and cell survival therefore critically depends on the concentration of proteins. To maintain constant protein concentrations during cell growth, global mRNA and protein synthesis rates are tightly linked to cell volume. While such regulation is appropriate for most proteins, certain cellular structures do not scale with cell volume. The most striking example of this is the genomic DNA, which doubles during the cell cycle and increases with ploidy, but is independent of cell volume. Here, we show that the amount of histone proteins is coupled to the DNA content, even though mRNA and protein synthesis globally increase with cell volume. As a consequence, and in contrast to the global trend, histone concentrations decrease with cell volume but increase with ploidy. We find that this distinct coordination of histone homeostasis and genome content is already achieved at the transcript level, and is an intrinsic property of histone promoters that does not require direct feedback mechanisms. Mathematical modeling and histone promoter truncations reveal a simple and generalizable mechanism to control the cell volume- and ploidy-dependence of a given gene through the balance of the initiation and elongation rates.

Comparative Genomic Insights Into the Taxonomic Classification, Diversity, and Secondary Metabolic Potentials of Kitasatospora, a Genus Closely Related to Streptomyces

While the genus Streptomyces (family Streptomycetaceae) has been studied as a model for bacterial secondary metabolism and genetics, its close relatives have been less studied. The genus Kitasatospora is the second largest genus in the family Streptomycetaceae. However, its taxonomic position within the family remains under debate and the secondary metabolic potential remains largely unclear. Here, we performed systematic comparative genomic and phylogenomic analyses of Kitasatospora. Firstly, the three genera within the family Streptomycetaceae (Kitasatospora, Streptomyces, and Streptacidiphilus) showed common genomic features, including high G + C contents, high secondary metabolic potentials, and high recombination frequencies. Secondly, phylogenomic and comparative genomic analyses revealed phylogenetic distinctions and genome content differences among these three genera, supporting Kitasatospora as a separate genus within the family. Lastly, the pan-genome analysis revealed extensive genetic diversity within the genus Kitasatospora, while functional annotation and genome content comparison suggested genomic differentiation among lineages. This study provided new insights into genomic characteristics of the genus Kitasatospora, and also uncovered its previously underestimated and complex secondary metabolism.

Machine learning approaches to predict the plant-associated phenotype of Xanthomonas strains

The genus Xanthomonas has long been considered to consist predominantly of plant pathogens, but over the last decade there has been an increasing number of reports on non-pathogenic and endophytic members. As Xanthomonas species are prevalent pathogens on a wide variety of important crops around the world, there is a need to distinguish between these plant-associated phenotypes. To date a large number of Xanthomonas genomes have been sequenced, which enables the application of machine learning (ML) approaches on the genome content to predict this phenotype. Until now such approaches to the pathogenomics of Xanthomonas strains have been hampered by the fragmentation of information regarding strain pathogenicity over many studies. Unification of this information into a single resource was therefore considered to be an essential step. Mining of 39 papers considering both plant-associated phenotypes, allowed for a phenotypic classification of 578 Xanthomonas strains. For 65 plant-pathogenic and 53 non-pathogenic strains the corresponding genomes were available and de novo annotated for the presence of Pfam protein domains used as features to train and compare three ML classification algorithms; CART, Lasso and Random Forest. Recursive feature extraction provided further insights into the virulence enabling factors, but also yielded domains linked to traits not present in pathogenic strains.

Hybrid Atypical Enteropathogenic and Extraintestinal Escherichia coli (aEPEC/ExPEC) BA1250 Strain: A Draft Genome

Diarrheagenic Escherichia coli is the major bacterial etiological agent of severe diarrhea and a major concern of public health. These pathogens have acquired genetic characteristics from other pathotypes, leading to unusual and singular genetic combinations, known as hybrid strains and may be more virulent due to a set of virulence factors from more than one pathotype. One of the possible combinations is with extraintestinal E. coli (ExPEC), a leading cause of urinary tract infection, often lethal after entering the bloodstream and atypical enteropathogenic E. coli (aEPEC), responsible for death of thousands of people every year, mainly children under five years old. Here we report the draft genome of a strain originally classified as aEPEC (BA1250) isolated from feces of a child with acute diarrhea. Phylogenetic analysis indicates that BA1250 genome content is genetically closer to E. coli strains that cause extraintestinal infections, other than intestinal infections. A deeper analysis showed that in fact this is a hybrid strain, due to the presence of a set of genes typically characteristic of ExPEC. These genomic findings expand our knowledge about aEPEC heterogeneity allowing further studies concerning E. coli pathogenicity and may be a source for future comparative studies, virulence characteristics, and evolutionary biology.