Analytical characterization of full, intermediate, and empty AAV capsids.

Manufacturing of recombinant adeno-associated virus (AAV) vectors produces three types of capsids: full, intermediate, and empty. While there are different opinions about the impact of intermediate and empty capsids on safety and efficacy of AAV products, they are generally considered impurities because they are not the intended fully intact vector product. The presence of these impurities could impact product efficacy due to potential competition with fully packaged AAVs for cellular transduction, as well as have potential implications to patient safety due to increased capsid load during dosing. To determine the impact of intermediate capsids on potency, an AAV preparation was separated into fractions enriched for full, intermediate, or empty capsids. Using a matrix of in vitro (infectivity, gene expression, biological activity) and in vivo potency assays to determine potency as a function of capsid content, our results indicate that while intermediate capsids contribute to the vector genome titer of the product and are equally as infectious as full capsids, they do not contribute to the potency of the AAV product. This study confirms the criticality of reducing and controlling the level of intermediate capsids to ensure a more efficacious AAV product.

Valhidepsin Lipopeptides from Chromobacterium vaccinii: Structures, Biosynthesis, and Coregulation with FR900359 Production.

Microbial secondary metabolites continue to provide a valuable source of both chemical matter and inspiration for drug discovery in a broad range of therapeutic areas. Beyond this, the corresponding microorganisms represent a sustainable modality for biotechnological production of structurally complex molecules at the quantities required for drug development or even commercial manufacturing. Chromobacterium vaccinii, which has recently been reported as a producer of the pharmacologically highly important Gq inhibitor FR900359 (FR), represents such an example. The characterization of an orphan biosynthetic gene cluster (BGC) located directly downstream of the frs BCG led to the discovery of eight new lipopeptides, valhidepsins A-H (1-8), produced by C. vaccinii. Their chemical structures were elucidated through analysis of 1D and 2D NMR data and high-resolution MS/MS fragmentation methods. The valhidepsins did not display significant antibiotic nor cytotoxic activities but showed surfactant properties. The cluster-compound correlation was demonstrated by generation of a knockout mutant, which abolished production of valhidepsins. This knockout mutant yielded a significantly increased isolated yield of FR.

Teleocidin-producing genotype of Streptomyces clavuligerus ATCC 27064.

Streptomyces clavuligerus is an industrially important producer of clavulanic acid (CA), a ß-lactamase inhibitor which is used together with amoxicillin in one of the most widely prescribed antibacterial medicines, the co-amoxiclav. In a mid-eighties ATCC vial of S. clavuligerus ATCC 27064 culture, we have found a new genotype, which was apparently lost from the subsequent ATCC collection stocks, and has remained obscure to the scientific community. Most importantly, this genotype harbors teleocidin (lyngbyatoxin) biosynthetic genes, which are located on an enigmatic 138 kb chromosomal region and support accumulation of significant amounts of these highly toxic, tumor-promoting secondary metabolites in cultures of S. clavuligerus. While this genomic region is completely absent from all published sequences for S. clavuligerus ATCC strain, at least one of the industrial strains for commercial production of CA, originating from ATCC 27064, retained the genetic potential for production of teleocidins. The origin of teleocidin biosynthetic cluster can now be traced back to early S. clavuligerus stocks at the ATCC. Our work provides a genome sequence and a deposited monoisolate of this genotype. Given the scale of industrial use of S. clavuligerus world-wide and toxicity of teleocidins, we also discuss the environmental and safety implications and provide a method of abolishing teleocidin production without affecting productivity of CA. KEY POINTS: • Early stocks of S. clavuligerus ATCC 27064 produce toxic teleocidins • Teleocidin biosynthetic genes were found within a distinct S. clavuligerus genotype • The genotype has been passed on to some industrial clavulanic acid producer strains.

Duplicated Enhancer Region Increases Expression of CTSB and Segregates with Keratolytic Winter Erythema in South African and Norwegian Families.

Keratolytic winter erythema (KWE) is a rare autosomal-dominant skin disorder characterized by recurrent episodes of palmoplantar erythema and epidermal peeling. KWE was previously mapped to 8p23.1-p22 (KWE critical region) in South African families. Using targeted resequencing of the KWE critical region in five South African families and SNP array and whole-genome sequencing in two Norwegian families, we identified two overlapping tandem duplications of 7.67 kb (South Africans) and 15.93 kb (Norwegians). The duplications segregated with the disease and were located upstream of CTSB, a gene encoding cathepsin B, a cysteine protease involved in keratinocyte homeostasis. Included in the 2.62 kb overlapping region of these duplications is an enhancer element that is active in epidermal keratinocytes. The activity of this enhancer correlated with CTSB expression in normal differentiating keratinocytes and other cell lines, but not with FDFT1 or NEIL2 expression. Gene expression (qPCR) analysis and immunohistochemistry of the palmar epidermis demonstrated significantly increased expression of CTSB, as well as stronger staining of cathepsin B in the stratum granulosum of affected individuals than in that of control individuals. Analysis of higher-order chromatin structure data and RNA polymerase II ChIA-PET data from MCF-7 cells did not suggest remote effects of the enhancer. In conclusion, KWE in South African and Norwegian families is caused by tandem duplications in a non-coding genomic region containing an active enhancer element for CTSB, resulting in upregulation of this gene in affected individuals.

Decatransin, a new natural product inhibiting protein translocation at the Sec61/SecYEG translocon.

A new cyclic decadepsipeptide was isolated from Chaetosphaeria tulasneorum with potent bioactivity on mammalian and yeast cells. Chemogenomic profiling in S. cerevisiae indicated that the Sec61 translocon complex, the machinery for protein translocation and membrane insertion at the endoplasmic reticulum, is the target. The profiles were similar to those of cyclic heptadepsipeptides of a distinct chemotype (including HUN-7293 and cotransin) that had previously been shown to inhibit cotranslational translocation at the mammalian Sec61 translocon. Unbiased, genome-wide mutagenesis followed by full-genome sequencing in both fungal and mammalian cells identified dominant mutations in Sec61p (yeast) or Sec61α1 (mammals) that conferred resistance. Most, but not all, of these mutations affected inhibition by both chemotypes, despite an absence of structural similarity. Biochemical analysis confirmed inhibition of protein translocation into the endoplasmic reticulum of both co- and post-translationally translocated substrates by both chemotypes, demonstrating a mechanism independent of a translating ribosome. Most interestingly, both chemotypes were found to also inhibit SecYEG, the bacterial Sec61 translocon homolog. We suggest 'decatransin' as the name for this new decadepsipeptide translocation inhibitor.

antiSMASH 3.0-a comprehensive resource for the genome mining of biosynthetic gene clusters.

Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.

Genome assembly of the bearded iris, Iris pallida Lam.

Irises are perennial plants, representing a large genus with hundreds of species. While cultivated extensively for their ornamental value, commercial interest in irises lies in the secondary metabolites present in their rhizomes. The Dalmatian Iris (Iris pallida Lam.) is an ornamental plant that also produces secondary metabolites with potential value to the fragrance and pharmaceutical industries. In addition to providing base notes for the fragrance industry, iris tissues and extracts possess antioxidant, anti-inflammatory and immunomodulatory effects. However, study of these secondary metabolites has been hampered by a lack of genomic information, requiring difficult extraction and analysis techniques. Here, we report the genome sequence of Iris pallida Lam., generated with Pacific Bioscience long-read sequencing, resulting in a 10.04-Gbp assembly with a scaffold N50 of 14.34 Mbp and 91.8% complete BUSCOs. This reference genome will allow researchers to study the biosynthesis of these secondary metabolites in much greater detail, opening new avenues of investigation for drug discovery and fragrance formulations.

SDRS--an algorithm for analyzing large-scale dose-response data.

SUMMARY: Dose-response information is critical to understanding drug effects, yet analytical methods for dose-response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoidal Dose Response Search (SDRS) algorithm, a grid search-based method designed to handle large-scale dose-response data. This method not only calculates the pharmacological parameters for every assay, but also provides built-in statistic that enables downstream systematic analyses, such as characterizing dose response at the transcriptome level. AVAILABILITY: Bio::SDRS is freely available from CPAN (www.cpan.org). CONTACTS: ruiruji@gmail.com; bruc@acm.org SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

Transcriptional profiling of the dose response: a more powerful approach for characterizing drug activities.

The dose response curve is the gold standard for measuring the effect of a drug treatment, but is rarely used in genomic scale transcriptional profiling due to perceived obstacles of cost and analysis. One barrier to examining transcriptional dose responses is that existing methods for microarray data analysis can identify patterns, but provide no quantitative pharmacological information. We developed analytical methods that identify transcripts responsive to dose, calculate classical pharmacological parameters such as the EC50, and enable an in-depth analysis of coordinated dose-dependent treatment effects. The approach was applied to a transcriptional profiling study that evaluated four kinase inhibitors (imatinib, nilotinib, dasatinib and PD0325901) across a six-logarithm dose range, using 12 arrays per compound. The transcript responses proved a powerful means to characterize and compare the compounds: the distribution of EC50 values for the transcriptome was linked to specific targets, dose-dependent effects on cellular processes were identified using automated pathway analysis, and a connection was seen between EC50s in standard cellular assays and transcriptional EC50s. Our approach greatly enriches the information that can be obtained from standard transcriptional profiling technology. Moreover, these methods are automated, robust to non-optimized assays, and could be applied to other sources of quantitative data.

Identification and application of threonine aldolase for synthesis of valuable α-amino, ß-hydroxy-building blocks.

Chiral ß-hydroxy α-amino acid structural motifs are interesting and common synthons present in multiple APIs and drug candidates. To access these chiral building blocks either multistep chemical syntheses are required or the application of threonine aldolases, which catalyze aldol reactions between an aldehyde and glycine. Bioinformatics tools have been utilized to identify the gene encoding threonine aldolase from Vanrija humicola and subsequent preparation of its recombinant version from E. coli fermentation. We planned to implement this enzyme as a key step to access the synthesis of our target API. Beyond this specific application, the aldolase was purified, characterized and the substrate scope of this enzyme further investigated. A number of enzymatic reactions were scaled-up and the products recovered to assess the diastereoselectivity and scalability of this asymmetric synthetic approach towards ß-hydroxy α-amino acid chiral building blocks.

Spatially constrained minimization of macromolecules.

A structural minimization procedure which converges rapidly and restricts the atomic shifts is outlined. It is implemented by adding a harmonic penalty term for the displacements of atomic positions and resetting the reference coordinates with respect to which the constraints are computed during the minimization. The resetting serves to reduce the constraint energy of the minimized structure to negligible levels.

FDR-FET: an optimizing gene set enrichment analysis method.

Gene set enrichment analysis for analyzing large profiling and screening experiments can reveal unifying biological schemes based on previously accumulated knowledge represented as "gene sets". Most of the existing implementations use a fixed fold-change or P value cutoff to generate regulated gene lists. However, the threshold selection in most cases is arbitrary, and has a significant effect on the test outcome and interpretation of the experiment. We developed a new gene set enrichment analysis method, ie, FDR-FET, which dynamically optimizes the threshold choice and improves the sensitivity and selectivity of gene set enrichment analysis. The procedure translates experimental results into a series of regulated gene lists at multiple false discovery rate (FDR) cutoffs, and computes the P value of the overrepresentation of a gene set using a Fisher's exact test (FET) in each of these gene lists. The lowest P value is retained to represent the significance of the gene set. We also implemented improved methods to define a more relevant global reference set for the FET. We demonstrate the validity of the method using a published microarray study of three protease inhibitors of the human immunodeficiency virus and compare the results with those from other popular gene set enrichment analysis algorithms. Our results show that combining FDR with multiple cutoffs allows us to control the error while retaining genes that increase information content. We conclude that FDR-FET can selectively identify significant affected biological processes. Our method can be used for any user-generated gene list in the area of transcriptome, proteome, and other biological and scientific applications.

Conserved fungal genes as potential targets for broad-spectrum antifungal drug discovery.

The discovery of novel classes of antifungal drugs depends to a certain extent on the identification of new, unexplored targets that are essential for growth of fungal pathogens. Likewise, the broad-spectrum capacity of future antifungals requires the target gene(s) to be conserved among key fungal pathogens. Using a genome comparison (or concordance) tool, we identified 240 conserved genes as candidates for potential antifungal targets in 10 fungal genomes. To facilitate the identification of essential genes in Candida albicans, we developed a repressible C. albicans MET3 (CaMET3) promoter system capable of evaluating gene essentiality on a genome-wide scale. The CaMET3 promoter was found to be highly amenable to controlled gene expression, a prerequisite for use in target-based whole-cell screening. When the expression of the known antifungal target C. albicans ERG1 was reduced via down-regulation of the CaMET3 promoter, the CaERG1 conditional mutant strain became hypersensitive, specifically to its inhibitor, terbinafine. Furthermore, parallel screening against a small compound library using the CaERG1 conditional mutant under normal and repressed conditions uncovered several hypersensitive compound hits. This work therefore demonstrates a streamlined process for proceeding from selection and validation of candidate antifungal targets to screening for specific inhibitors.