Evolutionary analyses of intrinsically disordered regions reveal widespread signals of conservation.

Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common "evolutionary signatures," i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.

Leveraging genomic redundancy to improve inference and alignment of orthologous proteins.

Identifying protein sequences with common ancestry is a core task in bioinformatics and evolutionary biology. However, methods for inferring and aligning such sequences in annotated genomes have not kept pace with the increasing scale and complexity of the available data. Thus, in this work, we implemented several improvements to the traditional methodology that more fully leverage the redundancy of closely related genomes and the organization of their annotations. Two highlights include the application of the more flexible k-clique percolation algorithm for identifying clusters of orthologous proteins and the development of a novel technique for removing poorly supported regions of alignments with a phylogenetic hidden Markov model (phylo-HMM). In making the latter, we wrote a fully documented Python package Homomorph that implements standard HMM algorithms and created a set of tutorials to promote its use by a wide audience. We applied the resulting pipeline to a set of 33 annotated Drosophila genomes, generating 22,813 orthologous groups and 8,566 high-quality alignments.

Metabolism and pharmacokinetics characterization of metarrestin in multiple species.

PURPOSE: Metarrestin is a first-in-class pyrrolo-pyrimidine-derived small molecule targeting a marker of genome organization associated with metastasis and is currently in preclinical development as an anti-cancer agent. Here, we report the in vitro ADME characteristics and in vivo pharmacokinetic behavior of metarrestin. METHODS: Solubility, permeability, and efflux ratio as well as in vitro metabolism of metarrestin in hepatocytes, liver microsomes and S9 fractions, recombinant cytochrome P450 (CYP) enzymes, and potential for CYP inhibition were evaluated. Single dose pharmacokinetic profiles after intravenous and oral administration in mice, rat, dog, monkey, and mini-pig were obtained. Simple allometric scaling was applied to predict human pharmacokinetics. RESULTS: Metarrestin had an aqueous solubility of 150 µM at pH 7.4, high permeability in PAMPA and moderate efflux ratio in Caco-2 assays. The compound was metabolically stable in liver microsomes, S9 fractions, and hepatocytes from six species, including human. Metarrestin is a CYP3A4 substrate and, in mini-pigs, is also directly glucuronidated. Metarrestin did not show cytochrome P450 inhibitory activity. Plasma concentration-time profiles showed low to moderate clearance, ranging from 0.6 mL/min/kg in monkeys to 48 mL/min/kg in mice and moderate to high volume of distribution, ranging from 1.5 L/kg in monkeys to 17 L/kg in mice. Metarrestin has greater than 80% oral bioavailability in all species tested. The excretion of unchanged parent drug in urine was < 5% in dogs and < 1% in monkeys over collection periods of ≥ 144 h; in bile-duct cannulated rats, the excretion of unchanged drug was < 1% in urine and < 2% in bile over a collection period of 48 h. CONCLUSIONS: Metarrestin is a low clearance compound which has good bioavailability and large biodistribution after oral administration. Biotransformation appears to be the major elimination process for the parent drug. In vitro data suggest a low drug-drug interaction potential on CYP-mediated metabolism. Overall favorable ADME and PK properties support metarrestin's progression to clinical investigation.

Phosphocyclocreatine is the dominant form of cyclocreatine in control and creatine transporter deficiency patient fibroblasts.

Creatine transporter deficiency (CTD) is a metabolic disorder resulting in cognitive, motor, and behavioral deficits. Cyclocreatine (cCr), a creatine analog, has been explored as a therapeutic strategy for the treatment of CTD. We developed a rapid, selective, and accurate HILIC ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method to simultaneously quantify the intracellular concentrations of cCr, creatine (Cr), creatine-d3 (Cr-d3), phosphocyclocreatine (pcCr), and phosphocreatine (pCr). Using HILIC-UPLC-MS/MS, we measured cCr and Cr-d3 uptake and their conversion to the phosphorylated forms in primary human control and CTD fibroblasts. Altogether, the data demonstrate that cCr enters cells and its dominant intracellular form is pcCr in both control and CTD patient cells. Therefore, cCr may replace creatine as a therapeutic strategy for the treatment of CTD.

Pharmacokinetic evaluation of the PNC disassembler metarrestin in wild-type and Pdx1-Cre;LSL-KrasG12D/+;Tp53R172H/+ (KPC) mice, a genetically engineered model of pancreatic cancer.

PURPOSE: Metarrestin is a first-in-class small molecule clinical candidate capable of disrupting the perinucleolar compartment, a subnuclear structure unique to metastatic cancer cells. This study aims to define the pharmacokinetic (PK) profile of metarrestin and the pharmacokinetic/pharmacodynamic relationship of metarrestin-regulated markers. METHODS: PK studies included the administration of single or multiple dose of metarrestin at 3, 10, or 25 mg/kg via intravenous (IV) injection, gavage (PO) or with chow to wild-type C57BL/6 mice and KPC mice bearing autochthonous pancreatic tumors. Metarrestin concentrations were analyzed by UPLC-MS/MS. Pharmacodynamic assays included mRNA expression profiling by RNA-seq and qRT-PCR for KPC mice. RESULTS: Metarrestin had a moderate plasma clearance of 48 mL/min/kg and a large volume of distribution of 17 L/kg at 3 mg/kg IV in C57BL/6 mice. The oral bioavailability after single-dose (SD) treatment was > 80%. In KPC mice treated with SD 25 mg/kg PO, plasma AUC0-∞ of 14400 ng h/mL, Cmax of 810 ng/mL and half-life (t1/2) of 8.5 h were observed. At 24 h after SD of 25 mg/kg PO, the intratumor concentration of metarrestin was high with a mean value of 6.2 µg/g tissue (or 13 µM), well above the cell-based IC50 of 0.4 µM. At multiple dose (MD) 25 mg/kg/day PO in KPC mice, mean tissue/plasma AUC0-24h ratio for tumor, spleen and liver was 37, 30 and 31, respectively. There was a good linear relationship of dosage to AUC0-24h and C24h. AUC0-24h MD to AUC0-24h SD ratios ranged from two for liver to five for tumor indicating additional accumulation in tumors. Dose-dependent normalization of FOXA1 and FOXO6 mRNA expression was observed in KPC tumors. CONCLUSIONS: Metarrestin is an effective therapeutic candidate with a favorable PK profile achieving excellent intratumor tissue levels in a disease with known poor drug delivery.

Preclinical Pharmacological Development of Chlorcyclizine Derivatives for the Treatment of Hepatitis C Virus Infection.

Hepatitis C virus (HCV) is a small, single-stranded, positive-sense RNA virus that infects more than an estimated 70 million people worldwide. Untreated, persistent HCV infection often results in chronic hepatitis, cirrhosis, or liver failure, with progression to hepatocellular carcinoma. Current anti-HCV regimens comprising direct acting antivirals (DAAs) can provide curative treatment; however, due to high costs there remains a need for effective, shorter-duration, and affordable treatments. Recently, we disclosed anti-HCV activity of the cheap antihistamine chlorcyclizine, targeting viral entry. Following our hit-to-lead optimization campaign, we report evaluation of preclinical in vitro absorption, distribution, metabolism, and excretion properties, and in vivo pharmacokinetic profiles of lead compounds. This led to selection of a new lead compound and evaluation of efficacy in chimeric mice engrafted with primary human hepatocytes infected with HCV. Further development and incorporation of this compound into DAA regimens has the potential to improve treatment efficacy, affordability, and accessibility.

The innate immune protein calprotectin promotes Pseudomonas aeruginosa and Staphylococcus aureus interaction.

Microorganisms form biofilms containing differentiated cell populations. To determine factors driving differentiation, we herein visualize protein and metal distributions within Pseudomonas aeruginosa biofilms using imaging mass spectrometry. These in vitro experiments reveal correlations between differential protein distribution and metal abundance. Notably, zinc- and manganese-depleted portions of the biofilm repress the production of anti-staphylococcal molecules. Exposure to calprotectin (a host protein known to sequester metal ions at infectious foci) recapitulates responses occurring within metal-deplete portions of the biofilm and promotes interaction between P. aeruginosa and Staphylococcus aureus. Consistent with these results, the presence of calprotectin promotes co-colonization of the murine lung, and polymicrobial communities are found to co-exist in calprotectin-enriched airspaces of a cystic fibrosis lung explant. These findings, which demonstrate that metal fluctuations are a driving force of microbial community structure, have clinical implications because of the frequent occurrence of P. aeruginosa and S. aureus co-infections.

Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families.

Phevor integrates phenotype, gene function, and disease information with personal genomic data for improved power to identify disease-causing alleles. Phevor works by combining knowledge resident in multiple biomedical ontologies with the outputs of variant-prioritization tools. It does so by using an algorithm that propagates information across and between ontologies. This process enables Phevor to accurately reprioritize potentially damaging alleles identified by variant-prioritization tools in light of gene function, disease, and phenotype knowledge. Phevor is especially useful for single-exome and family-trio-based diagnostic analyses, the most commonly occurring clinical scenarios and ones for which existing personal genome diagnostic tools are most inaccurate and underpowered. Here, we present a series of benchmark analyses illustrating Phevor's performance characteristics. Also presented are three recent Utah Genome Project case studies in which Phevor was used to identify disease-causing alleles. Collectively, these results show that Phevor improves diagnostic accuracy not only for individuals presenting with established disease phenotypes but also for those with previously undescribed and atypical disease presentations. Importantly, Phevor is not limited to known diseases or known disease-causing alleles. As we demonstrate, Phevor can also use latent information in ontologies to discover genes and disease-causing alleles not previously associated with disease.

The development of next-generation sequencing assays for the mitochondrial genome and 108 nuclear genes associated with mitochondrial disorders.

Sanger sequencing of multigenic disorders can be technically challenging, time consuming, and prohibitively expensive. High-throughput next-generation sequencing (NGS) can provide a cost-effective method for sequencing targeted genes associated with multigenic disorders. We have developed a NGS clinical targeted gene assay for the mitochondrial genome and for 108 selected nuclear genes associated with mitochondrial disorders. Mitochondrial disorders have a reported incidence of 1 in 5000 live births, encompass a broad range of phenotypes, and are attributed to mutations in the mitochondrial and nuclear genomes. Approximately 20% of mitochondrial disorders result from mutations in mtDNA, with the remaining 80% found in nuclear genes that affect mtDNA levels or mitochondrion protein assembly. In our NGS approach, the 16,569-bp mtDNA is enriched by long-range PCR and the 108 nuclear genes (which represent 1301 amplicons and 680 kb) are enriched by RainDance emulsion PCR. Sequencing is performed on Illumina HiSeq 2000 or MiSeq platforms, and bioinformatics analysis is performed using commercial and in-house developed bioinformatics pipelines. A total of 16 validation and 13 clinical samples were examined. All previously reported variants associated with mitochondrial disorders were found in validation samples, and 5 of the 13 clinical samples were found to have mutations associated with mitochondrial disorders in either the mitochondrial genome or the 108 nuclear genes. All variants were confirmed by Sanger sequencing.

A probabilistic disease-gene finder for personal genomes.

VAAST (the Variant Annotation, Analysis & Search Tool) is a probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST builds on existing amino acid substitution (AAS) and aggregative approaches to variant prioritization, combining elements of both into a single unified likelihood framework that allows users to identify damaged genes and deleterious variants with greater accuracy, and in an easy-to-use fashion. VAAST can score both coding and noncoding variants, evaluating the cumulative impact of both types of variants simultaneously. VAAST can identify rare variants causing rare genetic diseases, and it can also use both rare and common variants to identify genes responsible for common diseases. VAAST thus has a much greater scope of use than any existing methodology. Here we demonstrate its ability to identify damaged genes using small cohorts (n = 3) of unrelated individuals, wherein no two share the same deleterious variants, and for common, multigenic diseases using as few as 150 cases.

Global analysis of disease-related DNA sequence variation in 10 healthy individuals: implications for whole genome-based clinical diagnostics.

BACKGROUND: Understanding how sequence variants within healthy genomes are distributed with respect to ethnicity and disease-implicated genes is an essential first step toward establishing baselines for personalized genomic medicine. METHODS: In this study, we present an analysis of 10 genomes from healthy individuals of various ethnicities, produced using six different sequencing technologies. In total, these genomes contain more than 34 million single-nucleotide variants. RESULTS: We have analyzed these variants from a clinical perspective, assaying the influence of sequencing technology and ethnicity on prognosis. We have also examined the utility of OMIM and the disease-gene literature for determining the impact of rare, personal variants on an individual's health. CONCLUSIONS: Our analyses demonstrate that clinical prognoses are complicated by sequencing platform-specific errors and ethnicity. We show that disease-causing alleles are globally distributed along ethnic lines, with alleles known to be disease causing in Eurasians being significantly more likely to be homozygous in Africans.

Validation of DNA-based prognostic testing to predict spinal curve progression in adolescent idiopathic scoliosis.

STUDY DESIGN: Validation of a prognostic DNA marker panel. OBJECTIVE: The goals of this study were to develop and test the negative predictive value of a prognostic DNA test for adolescent idiopathic scoliosis (AIS) and to establish clinically meaningful endpoints for the test. SUMMARY OF BACKGROUND DATA: Clinical features do not adequately predict which children diagnosed with minimal or mild AIS will have the progressive form of the disease; genetic markers associated with curve progression might offer clinically useful prognostic insights. METHODS: Logistic regression was used to develop an algorithm to predict spinal curve progression incorporating genotypes for 53 single nucleotide polymorphisms and the patient's presenting spinal curve (Cobb angle). Three cohorts with known AIS outcomes were selected to reflect intended-use populations with various rates of AIS progression: 277 low-risk females representing a screening cohort, 257 females representing higher risk patients followed at referral centers, and 163 high risk males. DNA was extracted from saliva, and genotypes were determined using TaqMan assays. AIS Prognostic Test scores ranging from 1 to 200 were calculated. RESULTS: Low-risk scores (<41) had negative predictive values of 100%, 99%, and 97%, respectively, in the tested populations. In the risk model, we used cutoff scores of 50 and 180 to identify 75% of patients as low-risk (<1% risk of progressing to a surgical curve), 24% as intermediate-risk, and 1% as high-risk. CONCLUSION: Prognostic testing for AIS has the potential to reduce psychological trauma, serial exposure to diagnostic radiation, unnecessary treatments, and direct and indirect costs-of-care related to scoliosis monitoring in low-risk patients. Further improvements in test performance are expected as the optimal markers for each locus are identified and the underlying biologic pathways are better understood. The validity of the test applies only to white AIS patients; versions of the test optimized for AIS patients of other races have yet to be developed.