Accurate sequencing of DNA motifs able to form alternative (non-B) structures.

Approximately 13% of the human genome at certain motifs have the potential to form noncanonical (non-B) DNA structures (e.g., G-quadruplexes, cruciforms, and Z-DNA), which regulate many cellular processes but also affect the activity of polymerases and helicases. Because sequencing technologies use these enzymes, they might possess increased errors at non-B structures. To evaluate this, we analyzed error rates, read depth, and base quality of Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT) sequencing at non-B motifs. All technologies showed altered sequencing success for most non-B motif types, although this could be owing to several factors, including structure formation, biased GC content, and the presence of homopolymers. Single-nucleotide mismatch errors had low biases in HiFi and ONT for all non-B motif types but were increased for G-quadruplexes and Z-DNA in all three technologies. Deletion errors were increased for all non-B types but Z-DNA in Illumina and HiFi, as well as only for G-quadruplexes in ONT. Insertion errors for non-B motifs were highly, moderately, and slightly elevated in Illumina, HiFi, and ONT, respectively. Additionally, we developed a probabilistic approach to determine the number of false positives at non-B motifs depending on sample size and variant frequency, and applied it to publicly available data sets (1000 Genomes, Simons Genome Diversity Project, and gnomAD). We conclude that elevated sequencing errors at non-B DNA motifs should be considered in low-read-depth studies (single-cell, ancient DNA, and pooled-sample population sequencing) and in scoring rare variants. Combining technologies should maximize sequencing accuracy in future studies of non-B DNA.

Selection and thermostability suggest G-quadruplexes are novel functional elements of the human genome.

Approximately 1% of the human genome has the ability to fold into G-quadruplexes (G4s)-noncanonical strand-specific DNA structures forming at G-rich motifs. G4s regulate several key cellular processes (e.g., transcription) and have been hypothesized to participate in others (e.g., firing of replication origins). Moreover, G4s differ in their thermostability, and this may affect their function. Yet, G4s may also hinder replication, transcription, and translation and may increase genome instability and mutation rates. Therefore, depending on their genomic location, thermostability, and functionality, G4 loci might evolve under different selective pressures, which has never been investigated. Here we conducted the first genome-wide analysis of G4 distribution, thermostability, and selection. We found an overrepresentation, high thermostability, and purifying selection for G4s within genic components in which they are expected to be functional-promoters, CpG islands, and 5' and 3' UTRs. A similar pattern was observed for G4s within replication origins, enhancers, eQTLs, and TAD boundary regions, strongly suggesting their functionality. In contrast, G4s on the nontranscribed strand of exons were underrepresented, were unstable, and evolved neutrally. In general, G4s on the nontranscribed strand of genic components had lower density and were less stable than those on the transcribed strand, suggesting that the former are avoided at the RNA level. Across the genome, purifying selection was stronger at stable G4s. Our results suggest that purifying selection preserves the sequences of functional G4s, whereas nonfunctional G4s are too costly to be tolerated in the genome. Thus, G4s are emerging as fundamental, functional genomic elements.

An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data.

BACKGROUND: The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes. Recently, there have been numerous computational methods developed to predict human essential genes from population genomic data. While the existing methods are highly predictive of essential genes of long length, they have limited power in pinpointing short essential genes due to the sparsity of polymorphisms in the human genome. RESULTS: Motivated by the premise that population and functional genomic data may provide complementary evidence for gene essentiality, here we present an evolution-based deep learning model, DeepLOF, to predict essential genes in an unsupervised manner. Unlike previous population genetic methods, DeepLOF utilizes a novel deep learning framework to integrate both population and functional genomic data, allowing us to pinpoint short essential genes that can hardly be predicted from population genomic data alone. Compared with previous methods, DeepLOF shows unmatched performance in predicting ClinGen haploinsufficient genes, mouse essential genes, and essential genes in human cell lines. Notably, at a false positive rate of 5%, DeepLOF detects 50% more ClinGen haploinsufficient genes than previous methods. Furthermore, DeepLOF discovers 109 novel essential genes that are too short to be identified by previous methods. CONCLUSION: The predictive power of DeepLOF shows that it is a compelling computational method to aid in the discovery of essential genes.

Direct Incorporation of Dinitrogen into an Aliphatic C-H Bond.

The activation of dinitrogen (N2) and direct incorporation of its N atom into C-H bonds to create aliphatic C-N compounds remains unresolved. Incompatible conditions between dinitrogen reduction and C-H functionalization make this process extremely challenging. Herein, we report the first example of dinitrogen insertion into an aliphatic Csp3-H bond on the ligand scaffold of a 1,3-propane-bridged [N2N]2--type dititanium complex. Mechanistic investigations on the behaviors of dinuclear and mononuclear Ti complexes indicated the intramolecular synergistic effect of two Ti centers at a C-N bond-forming step. Computational studies revealed the critical isomerization between the inactive side-on N2 complex and the active nitridyl complex, which is responsible for the Csp3-H amination. This strategy maps an efficient route toward the future synthesis of aliphatic amines directly from N2.

Dissecting Genomic Determinants of Positive Selection with an Evolution-Guided Regression Model.

In evolutionary genomics, it is fundamentally important to understand how characteristics of genomic sequences, such as gene expression level, determine the rate of adaptive evolution. While numerous statistical methods, such as the McDonald-Kreitman (MK) test, are available to examine the association between genomic features and the rate of adaptation, we currently lack a statistical approach to disentangle the independent effect of a genomic feature from the effects of other correlated genomic features. To address this problem, I present a novel statistical model, the MK regression, which augments the MK test with a generalized linear model. Analogous to the classical multiple regression model, the MK regression can analyze multiple genomic features simultaneously to infer the independent effect of a genomic feature, holding constant all other genomic features. Using the MK regression, I identify numerous genomic features driving positive selection in chimpanzees. These features include well-known ones, such as local mutation rate, residue exposure level, tissue specificity, and immune genes, as well as new features not previously reported, such as gene expression level and metabolic genes. In particular, I show that highly expressed genes may have a higher adaptation rate than their weakly expressed counterparts, even though a higher expression level may impose stronger negative selection. Also, I show that metabolic genes may have a higher adaptation rate than their nonmetabolic counterparts, possibly due to recent changes in diet in primate evolution. Overall, the MK regression is a powerful approach to elucidate the genomic basis of adaptation.

Non-B DNA: a major contributor to small- and large-scale variation in nucleotide substitution frequencies across the genome.

Approximately 13% of the human genome can fold into non-canonical (non-B) DNA structures (e.g. G-quadruplexes, Z-DNA, etc.), which have been implicated in vital cellular processes. Non-B DNA also hinders replication, increasing errors and facilitating mutagenesis, yet its contribution to genome-wide variation in mutation rates remains unexplored. Here, we conducted a comprehensive analysis of nucleotide substitution frequencies at non-B DNA loci within noncoding, non-repetitive genome regions, their ±2 kb flanking regions, and 1-Megabase windows, using human-orangutan divergence and human single-nucleotide polymorphisms. Functional data analysis at single-base resolution demonstrated that substitution frequencies are usually elevated at non-B DNA, with patterns specific to each non-B DNA type. Mirror, direct and inverted repeats have higher substitution frequencies in spacers than in repeat arms, whereas G-quadruplexes, particularly stable ones, have higher substitution frequencies in loops than in stems. Several non-B DNA types also affect substitution frequencies in their flanking regions. Finally, non-B DNA explains more variation than any other predictor in multiple regression models for diversity or divergence at 1-Megabase scale. Thus, non-B DNA substantially contributes to variation in substitution frequencies at small and large scales. Our results highlight the role of non-B DNA in germline mutagenesis with implications to evolution and genetic diseases.

Unified inference of missense variant effects and gene constraints in the human genome.

A challenge in medical genomics is to identify variants and genes associated with severe genetic disorders. Based on the premise that severe, early-onset disorders often result in a reduction of evolutionary fitness, several statistical methods have been developed to predict pathogenic variants or constrained genes based on the signatures of negative selection in human populations. However, we currently lack a statistical framework to jointly predict deleterious variants and constrained genes from both variant-level features and gene-level selective constraints. Here we present such a unified approach, UNEECON, based on deep learning and population genetics. UNEECON treats the contributions of variant-level features and gene-level constraints as a variant-level fixed effect and a gene-level random effect, respectively. The sum of the fixed and random effects is then combined with an evolutionary model to infer the strength of negative selection at both variant and gene levels. Compared with previously published methods, UNEECON shows improved performance in predicting missense variants and protein-coding genes associated with autosomal dominant disorders, and feature importance analysis suggests that both gene-level selective constraints and variant-level predictors are important for accurate variant prioritization. Furthermore, based on UNEECON, we observe a low correlation between gene-level intolerance to missense mutations and that to loss-of-function mutations, which can be partially explained by the prevalence of disordered protein regions that are highly tolerant to missense mutations. Finally, we show that genes intolerant to both missense and loss-of-function mutations play key roles in the central nervous system and the autism spectrum disorders. Overall, UNEECON is a promising framework for both variant and gene prioritization.

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called Linear Allele-Specific Selection InferencE (LASSIE), for estimating the fitness effects of all observed and potential single-nucleotide variants, based on polymorphism data and predictive genomic features. We applied LASSIE to 51 high-coverage genome sequences annotated with 33 genomic features and constructed a map of allele-specific selection coefficients across all protein-coding sequences in the human genome. This map is generally consistent with previous inferences of the bulk distribution of fitness effects but reveals pervasive weak negative selection against synonymous mutations. In addition, the estimated selection coefficients are highly predictive of inherited pathogenic variants and cancer driver mutations, outperforming state-of-the-art variant prioritization methods. By contrasting our estimated model with ultrahigh coverage ExAC exome-sequencing data, we identified 1118 genes under unusually strong negative selection, which tend to be exclusively expressed in the central nervous system or associated with autism spectrum disorder, as well as 773 genes under unusually weak selection, which tend to be associated with metabolism. This combination of classical population genetic theory with modern machine-learning and large-scale genomic data is a powerful paradigm for the study of both human evolution and disease.

Characterizing RNA stability genome-wide through combined analysis of PRO-seq and RNA-seq data.

BACKGROUND: The concentrations of distinct types of RNA in cells result from a dynamic equilibrium between RNA synthesis and decay. Despite the critical importance of RNA decay rates, current approaches for measuring them are generally labor-intensive, limited in sensitivity, and/or disruptive to normal cellular processes. Here, we introduce a simple method for estimating relative RNA half-lives that is based on two standard and widely available high-throughput assays: Precision Run-On sequencing (PRO-seq) and RNA sequencing (RNA-seq). RESULTS: Our method treats PRO-seq as a measure of transcription rate and RNA-seq as a measure of RNA concentration, and estimates the rate of RNA decay required for a steady-state equilibrium. We show that this approach can be used to assay relative RNA half-lives genome-wide, with good accuracy and sensitivity for both coding and noncoding transcription units. Using a structural equation model (SEM), we test several features of transcription units, nearby DNA sequences, and nearby epigenomic marks for associations with RNA stability after controlling for their effects on transcription. We find that RNA splicing-related features are positively correlated with RNA stability, whereas features related to miRNA binding and DNA methylation are negatively correlated with RNA stability. Furthermore, we find that a measure based on U1 binding and polyadenylation sites distinguishes between unstable noncoding and stable coding transcripts but is not predictive of relative stability within the mRNA or lincRNA classes. We also identify several histone modifications that are associated with RNA stability. CONCLUSION: We introduce an approach for estimating the relative half-lives of individual RNAs. Together, our estimation method and systematic analysis shed light on the pervasive impacts of RNA stability on cellular RNA concentrations.

Phylogenetic Modeling of Regulatory Element Turnover Based on Epigenomic Data.

Evolutionary changes in gene expression are often driven by gains and losses of cis-regulatory elements (CREs). The dynamics of CRE evolution can be examined using multispecies epigenomic data, but so far such analyses have generally been descriptive and model-free. Here, we introduce a probabilistic modeling framework for the evolution of CREs that operates directly on raw chromatin immunoprecipitation and sequencing (ChIP-seq) data and fully considers the phylogenetic relationships among species. Our framework includes a phylogenetic hidden Markov model, called epiPhyloHMM, for identifying the locations of multiply aligned CREs, and a combined phylogenetic and generalized linear model, called phyloGLM, for accounting for the influence of a rich set of genomic features in describing their evolutionary dynamics. We apply these methods to previously published ChIP-seq data for the H3K4me3 and H3K27ac histone modifications in liver tissue from nine mammals. We find that enhancers are gained and lost during mammalian evolution at about twice the rate of promoters, and that turnover rates are negatively correlated with DNA sequence conservation, expression level, and tissue breadth, and positively correlated with distance from the transcription start site, consistent with previous findings. In addition, we find that the predicted dosage sensitivity of target genes positively correlates with DNA sequence constraint in CREs but not with turnover rates, perhaps owing to differences in the effect sizes of the relevant mutations. Altogether, our probabilistic modeling framework enables a variety of powerful new analyses.

Comparative analysis of the morphological and biomechanical properties of normal cornea and keratoconus at different stages.

PURPOSE: To compare the morphological and biomechanical properties of normal cornea and keratoconus at different stages. METHODS: A total of 408 patients (517 eyes) with keratoconus were included in this study. According to the Topographic Keratoconus (TKC) grading method, keratoconus was divided into stage I (TKC = 1, 130 eyes), stage II (TKC = 1-2, 2, 164 eyes), stage III (TKC = 2-3, 3, 125 eyes) and stage IV (TKC = 3-4, 4, 98 eyes). A total of 158 normal subjects (158 eyes) were recruited as the normal group. The corneal morphological parameters and biomechanical parameters were obtained with Scheimpflug tomography (Pentacam) and corneal visualization Scheimpflug technology (Corvis ST), and the receiver operating characteristic (ROC) curves were drawn. RESULTS: Each corneal morphological and most biomechanical parameters of the keratoconic eyes were significantly different from those of the normal eyes in this study (p < 0.001). ROC curve demonstrated that most parameters in this study showed high efficiency in diagnosing keratoconus (the area under the ROC (AUC) was > 0.9), with the Belin-Ambrósio deviation (BAD-D) and Tomographic and Biomechanical Index (TBI) showing higher efficiency. The efficiency of BAD-D and TBI was high in differentiating keratoconus at different stages (AUC > 0.963). The comparison of ROC curves of keratoconus at different stages did not reveal statistically significant differences for TBI. CONCLUSION: BAD-D and TBI can effectively diagnose stage I keratoconus. Moreover, the efficiency of TBI is the same in diagnosing keratoconus at all stages, while the diagnostic efficiency of other parameters increases with the increase in keratoconus stages.

Nascent RNA sequencing reveals a dynamic global transcriptional response at genes and enhancers to the natural medicinal compound celastrol.

Most studies of responses to transcriptional stimuli measure changes in cellular mRNA concentrations. By sequencing nascent RNA instead, it is possible to detect changes in transcription in minutes rather than hours and thereby distinguish primary from secondary responses to regulatory signals. Here, we describe the use of PRO-seq to characterize the immediate transcriptional response in human cells to celastrol, a compound derived from traditional Chinese medicine that has potent anti-inflammatory, tumor-inhibitory, and obesity-controlling effects. Celastrol is known to elicit a cellular stress response resembling the response to heat shock, but the transcriptional basis of this response remains unclear. Our analysis of PRO-seq data for K562 cells reveals dramatic transcriptional effects soon after celastrol treatment at a broad collection of both coding and noncoding transcription units. This transcriptional response occurred in two major waves, one within 10 min, and a second 40-60 min after treatment. Transcriptional activity was generally repressed by celastrol, but one distinct group of genes, enriched for roles in the heat shock response, displayed strong activation. Using a regression approach, we identified key transcription factors that appear to drive these transcriptional responses, including members of the E2F and RFX families. We also found sequence-based evidence that particular transcription factors drive the activation of enhancers. We observed increased polymerase pausing at both genes and enhancers, suggesting that pause release may be widely inhibited during the celastrol response. Our study demonstrates that a careful analysis of PRO-seq time-course data can disentangle key aspects of a complex transcriptional response, and it provides new insights into the activity of a powerful pharmacological agent.

PhastWeb: a web interface for evolutionary conservation scoring of multiple sequence alignments using phastCons and phyloP.

SUMMARY: The Phylogenetic Analysis with Space/Time models (PHAST) package is a widely used software package for comparative genomics that has been freely available for download since 2002. Here, we introduce a web interface (phastWeb) that makes it possible to use two of the most popular programs in PHAST, phastCons and phyloP, without downloading and installing the PHAST software. This interface allows users to upload a sequence alignment and either upload a corresponding phylogeny or have one estimated from the alignment. After processing, users can visualize alignments and conservation scores as genome browser tracks and download estimated tree models and raw scores for further analysis. Altogether, this resource makes key features of the PHAST package conveniently available to a broad audience. AVAILABILITY AND IMPLEMENTATION: PhastWeb is freely available on the web at http://compgen.cshl.edu/phastweb/. The website provides instructions as well as examples.

Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates.

The genomes of large numbers of single cells must be sequenced to further understanding of the biological significance of genomic heterogeneity in complex systems. Whole genome amplification (WGA) of single cells is generally the first step in such studies, but is prone to nonuniformity that can compromise genomic measurement accuracy. Despite recent advances, robust performance in high-throughput single-cell WGA remains elusive. Here, we introduce droplet multiple displacement amplification (MDA), a method that uses commercially available liquid dispensing to perform high-throughput single-cell MDA in nanoliter volumes. The performance of droplet MDA is characterized using a large dataset of 129 normal diploid cells, and is shown to exceed previously reported single-cell WGA methods in amplification uniformity, genome coverage, and/or robustness. We achieve up to 80% coverage of a single-cell genome at 5× sequencing depth, and demonstrate excellent single-nucleotide variant (SNV) detection using targeted sequencing of droplet MDA product to achieve a median allelic dropout of 15%, and using whole genome sequencing to achieve false and true positive rates of 9.66 × 10(-6) and 68.8%, respectively, in a G1-phase cell. We further show that droplet MDA allows for the detection of copy number variants (CNVs) as small as 30 kb in single cells of an ovarian cancer cell line and as small as 9 Mb in two high-grade serous ovarian cancer samples using only 0.02× depth. Droplet MDA provides an accessible and scalable method for performing robust and accurate CNV and SNV measurements on large numbers of single cells.

Intravitreous Delivery of Αb-Crystallin Ameliorates N-Methyl-N-Nitrosourea Induced Photoreceptor Degeneration in Mice: An in vivo and ex vivo Study.

BACKGROUND/AIMS: αB -crystallin (αBC) belongs to the family of small heat shock proteins that are necessary for maintaining oxygen homeostasis. This study was designed to explore the possible effects of αBC on N-methyl- N-nitrosourea (MNU) induced retinal degeneration and the underlying mechanisms. METHODS: The αBC was injected into the vitreous bodies of MNU administered mice. The retinal morphology and visual function of experimental animals were analyzed by electroretinography (ERG), Spectral domain optical coherence tomography (SD-OCT), fundus photographs, optokinetic testing and immunohistochemistry assay. RESULTS: Optokinetic behavioural tests and ERG examination suggested that the visual impairments of the MNU administered mice were ameliorated effectively by αBC treatment. OCT analysis showed that the major retinal architecture of the MNU administered mice was efficiently rescued by αBC treatment. Fundus examination suggested that the lesion size of the MNU administered mice was decreased by αBC treatment. MNU induced photoreceptor loss was also mitigated by αBC treatment as shown by hematoxylin and eosin staining. In particular, the immunostaining study suggested that M-cone photoreceptors, rather than the S-cone photoreceptors, were preferentially rescued, indicating that the photoreceptor populations have different sensitivities to αBC. The mechanism study suggested that the anti-apoptotic, anti-oxidative and neurotrophic function of αBC collectively contributed to these therapeutic effects. CONCLUSION: Intravitreal delivery of αBC could alleviate MNU induced photoreceptor degeneration and visual impairment. Further refinement of the αBC induced protection would afford a novel therapeutic strategy for retinitis pigmentosa.

Integrating Topographic Measures to Explore the Protective Effects of Peonidin Against the N-Methyl-N-Nitrosourea Induced Photoreceptor Degeneration.

BACKGROUND/AIMS: The pathphysiological properties of N-Methyl -N -nitrosourea (MNU) induced photoreceptor degeneration are similar to the hereditary retinitis pigmentosa (RP). The present study sought to explore the beneficial effects of the peonidin, a common aglycone form of anthocyanin, on the MNU induced photoreceptor degeneration via topographic measurements. METHODS: The MNU administrated mouse received peonidin or vehicle injections, and then they were examined by electroretinography (ERG), multi electrode array (MEA), histological and immunohistochemistry studies. RESULTS: The protective effects of peonidin on the MNU administrated retinas were systematically verified and quantified by topographic measures. The peonidin treatment could protect the photoreceptor against the MNU toxicity both functionally and morphologicaly. The most sensitive zone to peonidin therapy was sorted out, indicating that different rescuing kinetics existed between the retinal hemispheres and retinal quadrants. Moreover, the hyperactive spontaneous firing response and the debilitated light induced response in MNU administrated retinas could be partially reversed by peonidin treatment. To our knowledge, this was the first study to explore the pharmacological effects of peonidin on the electrophysiological properties of inner visual signal pathways. CONCLUSION: The peonidin could ameliorate the MNU induced photoreceptors degeneration and rectify the abnormities in the inner visual signal pathways. Future refinements of the knowledge cast insights into the discovery of a novel treatment for human RP.

The Vigabatrin Induced Retinal Toxicity is Associated with Photopic Exposure and Taurine Deficiency: An In Vivo Study.

BACKGROUND/AIMS: Retinal toxicity is one of the most commonly discussed and concerning adverse effects of vigabatrin (VGB). The present study explored the relationship between the VGB elicited retinal toxicity, photopic exposure, and taurine deficiency, aiming at screening for risk factors to minimize the adverse effects of VGB. METHODS: The effects of VGB on function and morphology of mouse retinas were examined via a series of in vivo tests, including electroretinography (ERG), Spectral domain optical coherence tomography (SD-OCT), and optokinetic testing. Moreover, VGB-treated mice were in addition treated with taurine to verify possible protective effects against retinal toxicity. RESULTS: A close relationship between VGB induced retinal toxicity and light exposure was observed. The VGB-treated mice which were reared in darkness preserved better visual function and retinal architectures as verified by the optokinetic tests, OCT and ERG examinations. The retinal taurine level of the VBG-treated mice which were exposed to light were significantly lower than that of the VBG mice reared in darkness. Furthermore, several in vivo evidence provided by our research confirmed that the VGB induced morphological and functional impairments could be partially alleviated by taurine treatment. The present study showed the retinal toxicity of VGB by in vivo measurements. CONCLUSION: The VGB induced retinal toxicity is closely associated with photopic exposure and taurine deficiency. Patients who are taking VGB might benefit from minimization of light exposure and dietetic taurine supplements.

FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures.

MOTIVATION: A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures. RESULTS: Both simulations and four case studies based on empirical data suggest that FuncPatch is a good approximation to GP4Rate. However, FuncPatch is orders of magnitudes faster than GP4Rate. In addition, simulations suggest that FuncPatch is potentially a useful tool complementary to Rate4Site, but the 3D sliding window method is less powerful than FuncPatch and Rate4Site. The functional patches predicted by FuncPatch in the four case studies are supported by experimental evidence, which corroborates the usefulness of FuncPatch. AVAILABILITY AND IMPLEMENTATION: The software FuncPatch is freely available at the web site, http://info.mcmaster.ca/yifei/FuncPatch CONTACT: golding@mcmaster.ca SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Hydrogen-Rich Saline as an Innovative Therapy for Cataract: A Hypothesis.

Cataract is the leading cause of irreversible blindness worldwide. Increasing evidence indicates that oxidative stress is an important risk factor contributing to the development of cataract. Moreover, the enhancement of the antioxidant defense system may be beneficial to prevent or delay the cataractogenesis. The term oxidative stress has been defined as a disturbance in the equilibrium status of oxidant/antioxidant systems with progressive accumulation of reactive oxygen species (ROS) in intact cells. Superfluous ROS can damage proteins, lipids, polysaccharides, and nucleic acids within ocular tissues that are closely correlated with cataract formation. Therefore, prevention of oxidative stress damage by antioxidants might be considered as a viable means of medically offsetting the progression of this vision-impairing disease. Molecular hydrogen has recently been verified to have protective and therapeutic value as an antioxidant through its ability to selectively reduce cytotoxic ROS such as hydroxyl radical (OH). Hitherto, hydrogen has been used as a therapeutic element against multiple pathologies in both animal models and human patients. Unlike most well-known antioxidants, which are unable to successfully target organelles, hydrogen has advantageous distribution characteristics enabling it to penetrate biomembranes and diffuse into the cytosol, mitochondria, and nucleus. Consequently, we speculate that hydrogen might be an effective antioxidant to protect against lens damage, and it is important to further explore the biological mechanism underlying its potential therapeutic effects.

Use of Hydrogen as a Novel Therapeutic Strategy Against Photoreceptor Degeneration in Retinitis Pigmentosa Patients.

Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterized by progressive photoreceptor apoptosis. Reactive oxygen species (ROS) have been recognized as critical initiators of the photoreceptor apoptosis in RP. Photoreceptor survival in RP mutants will not only require the inhibition of effectors of apoptotic machinery, but also the elimination of the initiating upstream signals, such as ROS. These cytotoxic ROS should be neutralized by the antioxidant defense system, otherwise they would interact with the macromolecules essential for photoreceptor survival. Hydrogen is a promising gaseous agent that has come to the forefront of therapeutic research over the last few years. It has been verified that hydrogen is capable of neutralizing the cytotoxic ROS selectively, rectifying abnormities in the apoptotic cascades, and attenuating the related inflammatory response. Hydrogen is so mild that it does not disturb the metabolic oxidation-reduction reactions or disrupt the physiologic ROS involved in cell signaling. Based on these findings, we hypothesize that hydrogen might be an effective therapeutic agent to slow or prevent photoreceptor degeneration in RP retinas. It is a logical step to test hydrogen for therapeutic use in multiple RP animal models, and ultimately in human RP patients.