Death Due to Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) Syndrome: A Case Report.

Background: Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a life-threatening, multi-organ adverse drug reaction with an incidence of 1 in 1000 to 1 in 10 000 high-risk drug exposures. Case Presentation: An elderly female presented to the hospital with progressive weakness and a diffuse erythematous macular rash covering most of her body that started 3 days prior. Over the next 3 days, the patient quickly deteriorated, developing disorientation with acute onset left-sided weakness, leukocytosis, thrombocytopenia, eosinophilia, liver and kidney failure, and hypoxia. Clinical and histological changes supported the diagnosis of DRESS syndrome caused by intravenous (IV) ampicillin administered during a prior hospitalization for a urinary tract infection. Systemic corticosteroids were initiated quickly thereafter, but the patient ultimately succumbed to complications caused by DRESS syndrome. Conclusion: There are currently no randomized trials evaluating treatments for DRESS, and evidenced-based guidelines are lacking. Viral reactivation has also been suggested as a possible complication of DRESS syndrome, though the true incidence and association remain unclear. Although we started our patient on high-dose IV corticosteroids early in her course, she still succumbed to complications of DRESS syndrome. Further research into the treatment of DRESS syndrome and its association with viral reactivation is essential.

Natural and engineered precision antibiotics in the context of resistance.

Antibiotics are essential weapons in our fight against infectious disease, yet the consequences of broad-spectrum antibiotic use on microbiome stability and pathogen resistance are prompting investigations into more selective alternatives. Echoing the advent of precision medicine in oncology, precision antibiotics with focused activities are emerging as a means of addressing infections without damaging microbiomes or incentivizing resistance. Historically, antibiotic design principles have been gleaned from Nature, and reinvestigation of overlooked antibacterials is now providing scaffolds and targets for the design of pathogen-specific drugs. In this perspective, we summarize the biosynthetic and antibacterial mechanisms used to access these activities, and discuss how such strategies may be co-opted through engineering approaches to afford precision antibiotics.

Ossifying Fibromyxoid Tumor: A Rare Subcutaneous Tumor.

Description The following case study demonstrates a 26-year-old male that presented to the dermatology clinic with an enlarging, raised skin nodule located on the left inferior lateral lower back. The patient reported it had persisted for two years, and he had not received prior treatment. He noted a family history of nonmelanoma skin cancer but had no other dermatological issues in the past. Physical examination revealed a pink, firm and well-circumscribed subcutaneous mass with a prominent follicular pore. It was assumed the lesion was an epidermal inclusion cyst, and surgical excision was performed. Histopathology revealed lobules of epithelioid cells with indistinct cytoplasm in a fibromyxoid hyalinized matrix surrounded by lamellar bone and a collagenous pseudocapsule. Immunohistochemical staining showed moderate desmin immunoreactivity and negative immunoreactivity for CD34, S-100, EMA, actin and pancytokeratin. Based on the findings, a diagnosis of ossifying fibromyxoid tumor was made. Given the uncertain biological potential of this lesion, re-excision was performed. No residual tumor was identified on repeat pathological evaluation. The patient was scheduled for close follow-up to survey for recurrence or possible metastasis.

Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences.

Novel antibiotics are urgently needed to address the looming global crisis of antibiotic resistance. Historically, the primary source of clinically used antibiotics has been microbial secondary metabolism. Microbial genome sequencing has revealed a plethora of uncharacterized natural antibiotics that remain to be discovered. However, the isolation of these molecules is hindered by the challenge of linking sequence information to the chemical structures of the encoded molecules. Here, we present PRISM 4, a comprehensive platform for prediction of the chemical structures of genomically encoded antibiotics, including all classes of bacterial antibiotics currently in clinical use. The accuracy of chemical structure prediction enables the development of machine-learning methods to predict the likely biological activity of encoded molecules. We apply PRISM 4 to chart secondary metabolite biosynthesis in a collection of over 10,000 bacterial genomes from both cultured isolates and metagenomic datasets, revealing thousands of encoded antibiotics. PRISM 4 is freely available as an interactive web application at http://prism.adapsyn.com .

Continuous bioactivity-dependent evolution of an antibiotic biosynthetic pathway.

Antibiotic biosynthetic gene clusters (BGCs) produce bioactive metabolites that impart a fitness advantage to their producer, providing a mechanism for natural selection. This selection drives antibiotic evolution and adapts BGCs for expression in different organisms, potentially providing clues to improve heterologous expression of antibiotics. Here, we use phage-assisted continuous evolution (PACE) to achieve bioactivity-dependent adaptation of the BGC for the antibiotic bicyclomycin (BCM), facilitating improved production in a heterologous host. This proof-of-principle study demonstrates that features of natural bioactivity-dependent evolution can be engineered to access unforeseen routes of improving metabolic pathways and product yields.

Red Ear Syndrome: A Case Presentation and Discussion.

Introduction: Red Ear Syndrome (RES) is a condition often considered to be a localized form of erythromelalgia. It can be related to structural cervical defects or idiopathic. RES is generally very difficult to treat. Discussion: A 57-year-old male presented to the dermatology clinic complaining of a 4-month history of intermittent redness and severe burning of bilateral ears. On examination, the patient exhibited edematous erythema and tenderness to palpation affecting the right and left ear and right malar cheek. A skin biopsy revealed mild superficial perivascular lymphocytic infiltrate with hypertrophy of endothelial cells. The patient was found to have a normal lab work-up including complete blood count, metabolic panel, erythrocyte sedimentation rate, anti-nuclear antibody and type II collagen antibody. A diagnosis of Red Ear Syndrome was made. After failing multiple medications over several months, the patient was started on aspirin and paroxetine which was gradually titrated until he was completely asymptomatic. To date, there is only one other case presentation illustrating the effectiveness of this treatment regimen. Conclusion: There are a limited number of cases describing idiopathic RES with inconsistent results in treatment. With a relatively small number of cases reported, further research is needed into the pathophysiology of RES along with the dual therapy of aspirin and paroxetine in patients that suffer from both primary and secondary RES.

A Case of Simpson-Golabi-Behmel Syndrome Presenting with Cutaneous Findings.

Description Simpson-Golabi-Behmel syndrome is a rare, X-linked recessive syndrome associated with mutations in the genes encoding glypican 3 (GPC3). The majority of cases have been described in pediatric males, with those affected showing manifestations of overgrowth, congenital heart defects, and increased incidence of neoplasia. Due to the X-linked nature of this disorder, penetrance is not well understood in female cases. Very few cases of female presentations of Simpson-Golabi-Behmel syndrome have been described, and this case highlights that there may be an association between mutated GPC3 carrier status and other cancers. We present a case of GPC3 gene mutation suggestive of Simpson-Golabi-Behmel syndrome in an adult female patient, diagnosed based on genetic testing performed due to a diagnosis of sebaceous carcinoma.

DeepRiPP integrates multiomics data to automate discovery of novel ribosomally synthesized natural products.

Microbial natural products represent a rich resource of evolved chemistry that forms the basis for the majority of pharmacotherapeutics. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) are a particularly interesting class of natural products noted for their unique mode of biosynthesis and biological activities. Analyses of sequenced microbial genomes have revealed an enormous number of biosynthetic loci encoding RiPPs but whose products remain cryptic. In parallel, analyses of bacterial metabolomes typically assign chemical structures to only a minority of detected metabolites. Aligning these 2 disparate sources of data could provide a comprehensive strategy for natural product discovery. Here we present DeepRiPP, an integrated genomic and metabolomic platform that employs machine learning to automate the selective discovery and isolation of novel RiPPs. DeepRiPP includes 3 modules. The first, NLPPrecursor, identifies RiPPs independent of genomic context and neighboring biosynthetic genes. The second module, BARLEY, prioritizes loci that encode novel compounds, while the third, CLAMS, automates the isolation of their corresponding products from complex bacterial extracts. DeepRiPP pinpoints target metabolites using large-scale comparative metabolomics analysis across a database of 10,498 extracts generated from 463 strains. We apply the DeepRiPP platform to expand the landscape of novel RiPPs encoded within sequenced genomes and to discover 3 novel RiPPs, whose structures are exactly as predicted by our platform. By building on advances in machine learning technologies, DeepRiPP integrates genomic and metabolomic data to guide the isolation of novel RiPPs in an automated manner.

Global analysis of prokaryotic tRNA-derived cyclodipeptide biosynthesis.

BACKGROUND: Among naturally occurring small molecules, tRNA-derived cyclodipeptides are a class that have attracted attention for their diverse and desirable biological activities. However, no tools are available to link cyclodipeptide synthases identified within prokaryotic genome sequences to their chemical products. Consequently, it is unclear how many genetically encoded cyclodipeptides represent novel products, and which producing organisms should be targeted for discovery. RESULTS: We developed a pipeline for identification and classification of cyclodipeptide biosynthetic gene clusters and prediction of aminoacyl-tRNA substrates and complete chemical structures. We leveraged this tool to conduct a global analysis of tRNA-derived cyclodipeptide biosynthesis in 93,107 prokaryotic genomes, and compared predicted cyclodipeptides to known cyclodipeptide synthase products and all known chemically characterized cyclodipeptides. By integrating predicted chemical structures and gene cluster architectures, we created a unified map of known and unknown genetically encoded cyclodipeptides. CONCLUSIONS: Our analysis suggests that sizeable regions of the chemical space encoded within sequenced prokaryotic genomes remain unexplored. Our map of the landscape of genetically encoded cyclodipeptides provides candidates for targeted discovery of novel compounds. The integration of our pipeline into a user-friendly web application provides a resource for further discovery of cyclodipeptides in newly sequenced prokaryotic genomes.

PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/.

Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching.

Polyketides (PKs) and nonribosomal peptides (NRPs) are profoundly important natural products, forming the foundations of many therapeutic regimes. Decades of research have revealed over 11,000 PK and NRP structures, and genome sequencing is uncovering new PK and NRP gene clusters at an unprecedented rate. However, only ∼10% of PK and NRPs are currently associated with gene clusters, and it is unclear how many of these orphan gene clusters encode previously isolated molecules. Therefore, to efficiently guide the discovery of new molecules, we must first systematically de-orphan emergent gene clusters from genomes. Here we provide to our knowledge the first comprehensive retro-biosynthetic program, generalized retro-biosynthetic assembly prediction engine (GRAPE), for PK and NRP families and introduce a computational pipeline, global alignment for natural products cheminformatics (GARLIC), to uncover how observed biosynthetic gene clusters relate to known molecules, leading to the identification of gene clusters that encode new molecules.

Genomic charting of ribosomally synthesized natural product chemical space facilitates targeted mining.

Microbial natural products are an evolved resource of bioactive small molecules, which form the foundation of many modern therapeutic regimes. Ribosomally synthesized and posttranslationally modified peptides (RiPPs) represent a class of natural products which have attracted extensive interest for their diverse chemical structures and potent biological activities. Genome sequencing has revealed that the vast majority of genetically encoded natural products remain unknown. Many bioinformatic resources have therefore been developed to predict the chemical structures of natural products, particularly nonribosomal peptides and polyketides, from sequence data. However, the diversity and complexity of RiPPs have challenged systematic investigation of RiPP diversity, and consequently the vast majority of genetically encoded RiPPs remain chemical "dark matter." Here, we introduce an algorithm to catalog RiPP biosynthetic gene clusters and chart genetically encoded RiPP chemical space. A global analysis of 65,421 prokaryotic genomes revealed 30,261 RiPP clusters, encoding 2,231 unique products. We further leverage the structure predictions generated by our algorithm to facilitate the genome-guided discovery of a molecule from a rare family of RiPPs. Our results provide the systematic investigation of RiPP genetic and chemical space, revealing the widespread distribution of RiPP biosynthesis throughout the prokaryotic tree of life, and provide a platform for the targeted discovery of RiPPs based on genome sequencing.

Duodenal Bacteria From Patients With Celiac Disease and Healthy Subjects Distinctly Affect Gluten Breakdown and Immunogenicity.

BACKGROUND & AIMS: Partially degraded gluten peptides from cereals trigger celiac disease (CD), an autoimmune enteropathy occurring in genetically susceptible persons. Susceptibility genes are necessary but not sufficient to induce CD, and additional environmental factors related to unfavorable alterations in the microbiota have been proposed. We investigated gluten metabolism by opportunistic pathogens and commensal duodenal bacteria and characterized the capacity of the produced peptides to activate gluten-specific T-cells from CD patients. METHODS: We colonized germ-free C57BL/6 mice with bacteria isolated from the small intestine of CD patients or healthy controls, selected for their in vitro gluten-degrading capacity. After gluten gavage, gliadin amount and proteolytic activities were measured in intestinal contents. Peptides produced by bacteria used in mouse colonizations from the immunogenic 33-mer gluten peptide were characterized by liquid chromatography tandem mass spectrometry and their immunogenic potential was evaluated using peripheral blood mononuclear cells from celiac patients after receiving a 3-day gluten challenge. RESULTS: Bacterial colonizations produced distinct gluten-degradation patterns in the mouse small intestine. Pseudomonas aeruginosa, an opportunistic pathogen from CD patients, exhibited elastase activity and produced peptides that better translocated the mouse intestinal barrier. P aeruginosa-modified gluten peptides activated gluten-specific T-cells from CD patients. In contrast, Lactobacillus spp. from the duodenum of non-CD controls degraded gluten peptides produced by human and P aeruginosa proteases, reducing their immunogenicity. CONCLUSIONS: Small intestinal bacteria exhibit distinct gluten metabolic patterns in vivo, increasing or reducing gluten peptide immunogenicity. This microbe-gluten-host interaction may modulate autoimmune risk in genetically susceptible persons and may underlie the reported association of dysbiosis and CD.

Mechanisms of Chromate, Selenate, and Sulfate Adsorption on Al-Substituted Ferrihydrite: Implications for Ferrihydrite Surface Structure and Reactivity.

Ferrihydrite is a nanocrystalline Fe (hydr)oxide and important sink for environmental contaminants. Although Fe (hydr)oxides are rarely pure in natural systems, little is known about the effects of structural impurities such as Al on the surface properties and reactivity of ferrihydrite. In this study, we characterized the adsorption mechanisms of chromate, selenate, and sulfate on Al-substituted ferrihydrite (0, 6, 12, 18, and 24 mol % Al) using in situ attenuated total reflection Fourier transform infrared spectroscopy. Spectral data sets recorded as a function of pH were processed using a multivariate curve resolution technique to identify which types of surface species form and to generate their concentration profiles as a function of pH and Al content. Results show a significant increase in relative fraction of outer-sphere complexes for all three oxyanions with increasing Al substitution. In addition, the effect of Al substitution is found to be mechanism-specific in the case of chromate, with bidentate complexes disproportionately suppressed over monodentate complexes at higher Al contents. Overall, our findings have important implications for the fate of chromate, selenate, and sulfate in subsurface environments and offer new insight into the surface reactivity of Al-ferrihydrite.

The role of counter ions in nano-hematite synthesis: Implications for surface area and selenium adsorption capacity.

Nano metal oxides are of interest for aqueous selenium (Se) remediation, and as such, nano-hematite (nα-Fe2O3) was examined for use as a Se adsorbent. The effect of surface area on adsorption was also studied. nα-Fe2O3 particles were synthesized from Fe(NO3)3 and FeCl3 via forced hydrolysis. The resulting particles have similar sizes, morphologies, aggregate size, pore size, and PZC. The nα-Fe2O3 from FeCl3 (nα-Fe2O3-C) differs from the nα-Fe2O3 from Fe(NO3)3 (nα-Fe2O3-N) with a ∼25±2m(2)/g greater surface area. Selenite Se(IV) adsorption capacity on nα-Fe2O3 has a qmax ∼17mg/g for the freeze-dried and re-suspended nα-Fe2O3. The Δqmax for nα-Fe2O3 from Fe(NO3)3 and FeCl3 that remained in suspension was 4.6mg/g. For selenate Se(VI), the freeze-dried and re-suspended particles realize a Δqmax= 1.5mg/g for nα-Fe2O3 from Fe(NO3)3 and FeCl3. The nα-Fe2O3 from Fe(NO3)3 and FeCl3 that remained in suspension demonstrated Se(VI) Δqmax=5.4mg/g. In situ ATR-FTIR isotherm measurements completed for Se(VI) at a pH 6 suggest that Se(VI) forms primarily outer-sphere complexes with nα-Fe2O3 synthesized from both salts.

Draft Genome Sequence of Streptomyces silvensis ATCC 53525, a Producer of Novel Hormone Antagonists.

Streptomyces silvensis produces nonribosomal peptides that act as antagonists of the human oxytocin and vasopressin receptors. Here, we present the genome sequence of S. silvensis ATCC 53525 and demonstrate that this organism possesses a number of additional biosynthetic gene clusters and might be a promising source for genome-guided drug discovery efforts.