Sorbitol Is a Severity Biomarker for PMM2-CDG with Therapeutic Implications.

OBJECTIVE: Epalrestat, an aldose reductase inhibitor increases phosphomannomutase (PMM) enzyme activity in a PMM2-congenital disorders of glycosylation (CDG) worm model. Epalrestat also decreases sorbitol level in diabetic neuropathy. We evaluated the genetic, biochemical, and clinical characteristics, including the Nijmegen Progression CDG Rating Scale (NPCRS), urine polyol levels and fibroblast glycoproteomics in patients with PMM2-CDG. METHODS: We performed PMM enzyme measurements, multiplexed proteomics, and glycoproteomics in PMM2-deficient fibroblasts before and after epalrestat treatment. Safety and efficacy of 0.8 mg/kg/day oral epalrestat were studied in a child with PMM2-CDG for 12 months. RESULTS: PMM enzyme activity increased post-epalrestat treatment. Compared with controls, 24% of glycopeptides had reduced abundance in PMM2-deficient fibroblasts, 46% of which improved upon treatment. Total protein N-glycosylation improved upon epalrestat treatment bringing overall glycosylation toward the control fibroblasts' glycosylation profile. Sorbitol levels were increased in the urine of 74% of patients with PMM2-CDG and correlated with the presence of peripheral neuropathy, and CDG severity rating scale. In the child with PMM2-CDG on epalrestat treatment, ataxia scores improved together with significant growth improvement. Urinary sorbitol levels nearly normalized in 3 months and blood transferrin glycosylation normalized in 6 months. INTERPRETATION: Epalrestat improved PMM enzyme activity, N-glycosylation, and glycosylation biomarkers in vitro. Leveraging cellular glycoproteome assessment, we provided a systems-level view of treatment efficacy and discovered potential novel biosignatures of therapy response. Epalrestat was well-tolerated and led to significant clinical improvements in the first pediatric patient with PMM2-CDG treated with epalrestat. We also propose urinary sorbitol as a novel biomarker for disease severity and treatment response in future clinical trials in PMM2-CDG. ANN NEUROL 20219999:n/a-n/a.

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG).

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders' views on AI for therapy discovery in CDG.

Doing it All - How Families are Reshaping Rare Disease Research.

The face of rare disease drug discovery and development is changing right before our eyes. The outliers of the past were the plucky parents who summoned up the courage to try to treat their children against all odds. Think of the rare disease focused movies 'Lorenzo's Oil' and 'Extraordinary Measures' but now accelerated to develop treatments even quicker. Parents, patient advocates and their collaborators are now capable of doing it all themselves. We think this will have profound implications for everyone from the incumbent rare disease foundations that have held sway for decades to the multibillion dollar rare disease market, BioPharma companies, VCs and angel investors that inhabit this space. The repercussions of this disruption will no doubt impact healthcare in general and ultimately influence how we develop treatments for major diseases as well. We present several lines of evidence for our viewpoint from our personal experiences interacting with many rare disease families and patient advocates in recent years.

GEX1A, a Polyketide from Streptomyces chromofuscus, Corrects the Cellular Defects Associated with Niemann-Pick Type C1 in Human Fibroblasts.

We report the first evidence of GEX1A, a polyketide known to modulate alternative pre-mRNA splicing, as a potential treatment for Niemann-Pick type C disease. GEX1A was isolated from its producing organism, Streptomyces chromofuscus, and screened in NPC1 mutant cells alongside several semisynthetic analogues. We found that GEX1A and analogues are capable of restoring cholesterol trafficking in NPC1 mutant fibroblasts, as well as altering the expression of NPC1 isoforms detected by Western blot. These results, along with the compound's favorable pharmacokinetic properties, highlight the potential of spliceosome-targeting scaffolds such as GEX1A for the treatment of genetic diseases.

Genetic basis of individual differences in the response to small-molecule drugs in yeast.

Individual response to small-molecule drugs is variable; a drug that provides a cure for some may confer no therapeutic benefit or trigger an adverse reaction in others. To begin to understand such differences systematically, we treated 104 genotyped segregants from a cross between two yeast strains with a collection of 100 diverse small molecules. We used linkage analysis to identify 124 distinct linkages between genetic markers and response to 83 compounds. The linked markers clustered at eight genomic locations, or quantitative-trait locus 'hotspots', that contain one or more polymorphisms that affect response to multiple small molecules. We also experimentally verified that a deficiency in leucine biosynthesis caused by a deletion of LEU2 underlies sensitivity to niguldipine, which is structurally related to therapeutic calcium channel blockers, and that a natural coding-region polymorphism in the inorganic phosphate transporter PHO84 underlies sensitivity to two polychlorinated phenols that uncouple oxidative phosphorylation. Our results provide a step toward a systematic understanding of small-molecule drug action in genetically distinct individuals.

Evolutionary rescue of phosphomannomutase deficiency in yeast models of human disease.

The most common cause of human congenital disorders of glycosylation (CDG) are mutations in the phosphomannomutase gene PMM2, which affect protein N-linked glycosylation. The yeast gene SEC53 encodes a homolog of human PMM2. We evolved 384 populations of yeast harboring one of two human-disease-associated alleles, sec53-V238M and sec53-F126L, or wild-type SEC53. We find that after 1000 generations, most populations compensate for the slow-growth phenotype associated with the sec53 human-disease-associated alleles. Through whole-genome sequencing we identify compensatory mutations, including known SEC53 genetic interactors. We observe an enrichment of compensatory mutations in other genes whose human homologs are associated with Type 1 CDG, including PGM1, which encodes the minor isoform of phosphoglucomutase in yeast. By genetic reconstruction, we show that evolved pgm1 mutations are dominant and allele-specific genetic interactors that restore both protein glycosylation and growth of yeast harboring the sec53-V238M allele. Finally, we characterize the enzymatic activity of purified Pgm1 mutant proteins. We find that reduction, but not elimination, of Pgm1 activity best compensates for the deleterious phenotypes associated with the sec53-V238M allele. Broadly, our results demonstrate the power of experimental evolution as a tool for identifying genes and pathways that compensate for human-disease-associated alleles.

Glial control of sphingolipid levels sculpts diurnal remodeling in a circadian circuit.

Structural plasticity in the brain often necessitates dramatic remodeling of neuronal processes, with attendant reorganization of the cytoskeleton and membranes. Although cytoskeletal restructuring has been studied extensively, how lipids might orchestrate structural plasticity remains unclear. We show that specific glial cells in Drosophila produce glucocerebrosidase (GBA) to locally catabolize sphingolipids. Sphingolipid accumulation drives lysosomal dysfunction, causing gba1b mutants to harbor protein aggregates that cycle across circadian time and are regulated by neural activity, the circadian clock, and sleep. Although the vast majority of membrane lipids are stable across the day, a specific subset that is highly enriched in sphingolipids cycles daily in a gba1b-dependent fashion. Remarkably, both sphingolipid biosynthesis and degradation are required for the diurnal remodeling of circadian clock neurites, which grow and shrink across the day. Thus, dynamic sphingolipid regulation by glia enables diurnal circuit remodeling and proper circadian behavior.

Harnessing gene expression to identify the genetic basis of drug resistance.

The advent of cost-effective genotyping and sequencing methods have recently made it possible to ask questions that address the genetic basis of phenotypic diversity and how natural variants interact with the environment. We developed Camelot (CAusal Modelling with Expression Linkage for cOmplex Traits), a statistical method that integrates genotype, gene expression and phenotype data to automatically build models that both predict complex quantitative phenotypes and identify genes that actively influence these traits. Camelot integrates genotype and gene expression data, both generated under a reference condition, to predict the response to entirely different conditions. We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug-free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene-drug interactions. Our approach is robust, applicable to other phenotypes and species, and has potential for applications in personalized medicine, for example, in predicting how an individual will respond to a previously unseen drug.

Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast.

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor's phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time.

Yeast Models of Phosphomannomutase 2 Deficiency, a Congenital Disorder of Glycosylation.

Phosphomannomutase 2 Deficiency (PMM2-CDG) is the most common monogenic congenital disorder of glycosylation (CDG) affecting at least 800 patients globally. PMM2 orthologs are present in model organisms, including the budding yeast Saccharomyces cerevisiae gene SEC53 Here we describe conserved genotype-phenotype relationships across yeast and human patients between five PMM2 loss-of-function missense mutations and their orthologous SEC53 mutations. These alleles range in severity from folding defective (hypomorph) to dimerization defective (severe hypomorph) to catalytic dead (null). We included the first and second most common missense mutations - R141H, F119L respectively- and the most common compound heterozygote genotype - PMM2R141H/F119L - observed in PMM2-CDG patients. Each mutation described is expressed in haploid as well as homozygous and heterozygous diploid yeast cells at varying protein expression levels as either SEC53 protein variants or PMM2 protein variants. We developed a 384-well-plate, growth-based assay for use in a screen of the 2,560-compound Microsource Spectrum library of approved drugs, experimental drugs, tool compounds and natural products. We identified three compounds that suppress growth defects of SEC53 variants, F126L and V238M, based on the biochemical defect of the allele, protein abundance or ploidy. The rare PMM2 E139K protein variant is fully functional in yeast cells, suggesting that its pathogenicity in humans is due to the underlying DNA mutation that results in skipping of exon 5 and a nonfunctional truncated protein. Together, these results demonstrate that yeast models can be used to characterize known and novel PMM2 patient alleles in quantitative growth and enzymatic activity assays, and used as patient avatars for PMM2-CDG drug screens yielding compounds that could be rapidly cross-validated in zebrafish, rodent and human organoid models.

Drug screens of NGLY1 deficiency in worm and fly models reveal catecholamine, NRF2 and anti-inflammatory-pathway activation as potential clinical approaches.

N-glycanase 1 (NGLY1) deficiency is an ultra-rare and complex monogenic glycosylation disorder that affects fewer than 40 patients globally. NGLY1 deficiency has been studied in model organisms such as yeast, worms, flies and mice. Proteasomal and mitochondrial homeostasis gene networks are controlled by the evolutionarily conserved transcriptional regulator NRF1, whose activity requires deglycosylation by NGLY1. Hypersensitivity to the proteasome inhibitor bortezomib is a common phenotype observed in whole-animal and cellular models of NGLY1 deficiency. Here, we describe unbiased phenotypic drug screens to identify FDA-approved drugs that are generally recognized as safe natural products, and novel chemical entities, that rescue growth and development of NGLY1-deficient worm and fly larvae treated with a toxic dose of bortezomib. We used image-based larval size and number assays for use in screens of a 2560-member drug-repurposing library and a 20,240-member lead-discovery library. A total of 91 validated hit compounds from primary invertebrate screens were tested in a human cell line in an NRF2 activity assay. NRF2 is a transcriptional regulator that regulates cellular redox homeostasis, and it can compensate for loss of NRF1. Plant-based polyphenols make up the largest class of hit compounds and NRF2 inducers. Catecholamines and catecholamine receptor activators make up the second largest class of hits. Steroidal and non-steroidal anti-inflammatory drugs make up the third largest class. Only one compound was active in all assays and species: the atypical antipsychotic and dopamine receptor agonist aripiprazole. Worm and fly models of NGLY1 deficiency validate therapeutic rationales for activation of NRF2 and anti-inflammatory pathways based on results in mice and human cell models, and suggest a novel therapeutic rationale for boosting catecholamine levels and/or signaling in the brain.

Repurposing the aldose reductase inhibitor and diabetic neuropathy drug epalrestat for the congenital disorder of glycosylation PMM2-CDG.

Phosphomannomutase 2 deficiency, or PMM2-CDG, is the most common congenital disorder of glycosylation and affects over 1000 patients globally. There are no approved drugs that treat the symptoms or root cause of PMM2-CDG. To identify clinically actionable compounds that boost human PMM2 enzyme function, we performed a multispecies drug repurposing screen using a novel worm model of PMM2-CDG, followed by PMM2 enzyme functional studies in PMM2-CDG patient fibroblasts. Drug repurposing candidates from this study, and drug repurposing candidates from a previously published study using yeast models of PMM2-CDG, were tested for their effect on human PMM2 enzyme activity in PMM2-CDG fibroblasts. Of the 20 repurposing candidates discovered in the worm-based phenotypic screen, 12 were plant-based polyphenols. Insights from structure-activity relationships revealed epalrestat, the only antidiabetic aldose reductase inhibitor approved for use in humans, as a first-in-class PMM2 enzyme activator. Epalrestat increased PMM2 enzymatic activity in four PMM2-CDG patient fibroblast lines with genotypes R141H/F119L, R141H/E139K, R141H/N216I and R141H/F183S. PMM2 enzyme activity gains ranged from 30% to 400% over baseline, depending on genotype. Pharmacological inhibition of aldose reductase by epalrestat may shunt glucose from the polyol pathway to glucose-1,6-bisphosphate, which is an endogenous stabilizer and coactivator of PMM2 homodimerization. Epalrestat is a safe, oral and brain penetrant drug that was approved 27 years ago in Japan to treat diabetic neuropathy in geriatric populations. We demonstrate that epalrestat is the first small molecule activator of PMM2 enzyme activity with the potential to treat peripheral neuropathy and correct the underlying enzyme deficiency in a majority of pediatric and adult PMM2-CDG patients.

Defects in the Neuroendocrine Axis Contribute to Global Development Delay in a Drosophila Model of NGLY1 Deficiency.

N-glycanase 1 (NGLY1) Deficiency is a rare monogenic multi-system disorder first described in 2014. NGLY1 is evolutionarily conserved in model organisms. Here we conducted a natural history study and chemical-modifier screen on the Drosophila melanogaster NGLY1 homolog, Pngl We generated a new fly model of NGLY1 Deficiency, engineered with a nonsense mutation in Pngl at codon 420 that results in a truncation of the C-terminal carbohydrate-binding PAW domain. Homozygous mutant animals exhibit global development delay, pupal lethality and small body size as adults. We developed a 96-well-plate, image-based, quantitative assay of Drosophila larval size for use in a screen of the 2,650-member Microsource Spectrum compound library of FDA approved drugs, bioactive tool compounds, and natural products. We found that the cholesterol-derived ecdysteroid molting hormone 20-hydroxyecdysone (20E) partially rescued the global developmental delay in mutant homozygotes. Targeted expression of a human NGLY1 transgene to tissues involved in ecdysteroidogenesis, e.g., prothoracic gland, also partially rescues global developmental delay in mutant homozygotes. Finally, the proteasome inhibitor bortezomib is a potent enhancer of global developmental delay in our fly model, evidence of a defective proteasome "bounce-back" response that is also observed in nematode and cellular models of NGLY1 Deficiency. Together, these results demonstrate the therapeutic relevance of a new fly model of NGLY1 Deficiency for drug discovery and gene modifier screens.

Revealing complex traits with small molecules and naturally recombinant yeast strains.

Here we demonstrate that natural variants of the yeast Saccharomyces cerevisiae are a model system for the systematic study of complex traits, specifically the response to small molecules. As a complement to artificial knockout collections of S. cerevisiae widely used to study individual gene function, we used 314- and 1932-member libraries of mutant strains generated by meiotic recombination to study the cumulative, quantitative effects of natural mutations on phenotypes induced by 23 small-molecule perturbagens (SMPs). This approach reveals synthetic lethality between SMPs, and genetic mapping studies confirm the involvement of multiple quantitative trait loci in the response to two SMPs that affect respiratory processes. The systematic combination of natural variants of yeast and small molecules that modulate evolutionarily conserved cellular processes can enable a better understanding of the general features of complex traits.

Anatomy of the Crowd4Discovery crowdfunding campaign.

Crowdfunding allows the public to fund creative projects, including curiosity-driven scientific research. Last Fall, I was part of a team that raised $25,460 from an international coalition of "micropatrons" for an open, pharmacological research project called Crowd4Discovery. The goal of Crowd4Discovery is to determine the precise location of amphetamines inside mouse brain cells, and we are sharing the results of this project on the Internet as they trickle in. In this commentary, I will describe the genesis of Crowd4Discovery, our motivations for crowdfunding, an analysis of our fundraising data, and the nuts and bolts of running a crowdfunding campaign. Science crowdfunding is in its infancy but has already been successfully used by an array of scientists in academia and in the private sector as both a supplement and a substitute to grants. With traditional government sources of funding for basic scientific research contracting, an alternative model that couples fundraising and outreach - and in the process encourages more openness and accountability - may be increasingly attractive to researchers seeking to diversify their funding streams.

Accumulation of an antidepressant in vesiculogenic membranes of yeast cells triggers autophagy.

Many antidepressants are cationic amphipaths, which spontaneously accumulate in natural or reconstituted membranes in the absence of their specific protein targets. However, the clinical relevance of cellular membrane accumulation by antidepressants in the human brain is unknown and hotly debated. Here we take a novel, evolutionarily informed approach to studying the effects of the selective-serotonin reuptake inhibitor sertraline/Zoloft® on cell physiology in the model eukaryote Saccharomyces cerevisiae (budding yeast), which lacks a serotonin transporter entirely. We biochemically and pharmacologically characterized cellular uptake and subcellular distribution of radiolabeled sertraline, and in parallel performed a quantitative ultrastructural analysis of organellar membrane homeostasis in untreated vs. sertraline-treated cells. These experiments have revealed that sertraline enters yeast cells and then reshapes vesiculogenic membranes by a complex process. Internalization of the neutral species proceeds by simple diffusion, is accelerated by proton motive forces generated by the vacuolar H(+)-ATPase, but is counteracted by energy-dependent xenobiotic efflux pumps. At equilibrium, a small fraction (10-15%) of reprotonated sertraline is soluble while the bulk (90-85%) partitions into organellar membranes by adsorption to interfacial anionic sites or by intercalation into the hydrophobic phase of the bilayer. Asymmetric accumulation of sertraline in vesiculogenic membranes leads to local membrane curvature stresses that trigger an adaptive autophagic response. In mutants with altered clathrin function, this adaptive response is associated with increased lipid droplet formation. Our data not only support the notion of a serotonin transporter-independent component of antidepressant function, but also enable a conceptual framework for characterizing the physiological states associated with chronic but not acute antidepressant administration in a model eukaryote.

The antidepressant sertraline targets intracellular vesiculogenic membranes in yeast.

Numerous studies have shown that the clinical antidepressant sertraline (Zoloft) is biologically active in model systems, including fungi, which do not express its putative protein target, the serotonin/5-HT transporter, thus demonstrating the existence of one or more secondary targets. Here we show that in the absence of its putative protein target, sertraline targets phospholipid membranes that comprise the acidic organelles of the intracellular vesicle transport system by a mechanism consistent with the bilayer couple hypothesis. On the basis of a combination of drug-resistance selection and chemical-genomic screening, we hypothesize that loss of vacuolar ATPase activity reduces uptake of sertraline into cells, whereas dysregulation of clathrin function reduces the affinity of membranes for sertraline. Remarkably, sublethal doses of sertraline stimulate growth of mutants with impaired clathrin function. Ultrastructural studies of sertraline-treated cells revealed a phenotype that resembles phospholipidosis induced by cationic amphiphilic drugs in mammalian cells. Using reconstituted enzyme assays, we also demonstrated that sertraline inhibits phospholipase A(1) and phospholipase D, exhibits mixed effects on phospholipase C, and activates phospholipase A(2). Overall, our study identifies two evolutionarily conserved membrane--active processes-vacuolar acidification and clathrin-coat formation--as modulators of sertraline's action at membranes.

Using expression and genotype to predict drug response in yeast.

Personalized, or genomic, medicine entails tailoring pharmacological therapies according to individual genetic variation at genomic loci encoding proteins in drug-response pathways. It has been previously shown that steady-state mRNA expression can be used to predict the drug response (i.e., sensitivity or resistance) of non-genotyped mammalian cancer cell lines to chemotherapeutic agents. In a real-world setting, clinicians would have access to both steady-state expression levels of patient tissue(s) and a patient's genotypic profile, and yet the predictive power of transcripts versus markers is not well understood. We have previously shown that a collection of genotyped and expression-profiled yeast strains can provide a model for personalized medicine. Here we compare the predictive power of 6,229 steady-state mRNA transcript levels and 2,894 genotyped markers using a pattern recognition algorithm. We were able to predict with over 70% accuracy the drug sensitivity of 104 individual genotyped yeast strains derived from a cross between a laboratory strain and a wild isolate. We observe that, independently of drug mechanism of action, both transcripts and markers can accurately predict drug response. Marker-based prediction is usually more accurate than transcript-based prediction, likely reflecting the genetic determination of gene expression in this cross.

Quantifying fitness distributions and phenotypic relationships in recombinant yeast populations.

Studies of the role of sex in evolution typically involve a longitudinal comparison of a single ancestor to several intermediate descendants and to one terminally evolved descendant after many generations of adaptation under a given selective regime. Here we take a complementary, statistical approach to sex in evolution, by describing the distribution of phenotypic similarity in a population of yeast F1 meiotic recombinants. By applying graph theory to fitness measurements of thousands of Saccharomyces cerevisiae recombinants treated with 10 mechanistically distinct, growth-inhibitory small-molecule perturbagens (SMPs), we show that the network of phenotypic similarity among F1 recombinants exhibits a scale-free degree distribution. F1 recombinants are often phenotypically unique and sometimes exceptional, and their fitness strengths are unevenly distributed across the 10 compound treatments. By contrast, highly phenotypically similar F1 recombinants constitute failing hubs that display below-average fitness across all compound treatments and are candidate substrates for purifying selection. Comparison of the F1 generation with the parental strains reveals that (i) there is a specialist more fit in any given single condition than any of the parents but (ii) only rarely are there generalists that exhibit greater fitness than both parental strains across a majority of conditions. This analysis allows us to evaluate and to gain better theoretical understanding of the costs and benefits of sex in the F1 generation.