Why are complementary DNA strands symmetric?

MOTIVATION: Over sufficiently long windows, complementary strands of DNA tend to have the same base composition. A few reports have indicated that this first-order parity rule extends at higher orders to oligonucleotide composition, at least in some organisms or taxa. However, the scientific literature falls short of providing a comprehensive study of reverse-complement symmetry at multiple orders and across the kingdom of life. It also lacks a characterization of this symmetry and a convincing explanation or clarification of its origin. RESULTS: We develop methods to measure and characterize symmetry at multiple orders, and analyze a wide set of genomes, encompassing single- and double-stranded RNA and DNA viruses, bacteria, archae, mitochondria, and eukaryota. We quantify symmetry at orders 1 to 9 for contiguous sequences and pools of coding and non-coding upstream regions, compare the observed symmetry levels to those predicted by simple statistical models, and factor out the effect of lower-order distributions. We establish the universality and variability range of first-order strand symmetry, as well as of its higher-order extensions, and demonstrate the existence of genuine high-order symmetric constraints. We show that ubiquitous reverse-complement symmetry does not result from a single cause, such as point mutation or recombination, but rather emerges from the combined effects of a wide spectrum of mechanisms operating at multiple orders and length scales.     

Assessing the accuracy of prediction algorithms for classification: an overview

We provide a unified overview of methods that currently are widely used to assess the accuracy of prediction algorithms, from raw percentages, quadratic error measures and other distances, and correlation coefficients, and to information theoretic measures such as relative entropy and mutual information. We briefly discuss the advantages and disadvantages of each approach. For classification tasks, we derive new learning algorithms for the design of prediction systems by directly optimising the correlation coefficient. We observe and prove several results relating sensitivity and specificity of optimal systems. While the principles are general, we illustrate the applicability on specific problems such as protein secondary structure and signal peptide prediction.     

Optimizing efficacy of quick parathyroid hormone determination in the operating theater

The usefulness of intraoperative parathyroid hormone (PTH) monitoring has been extensively documented in primary hyperparathyroidism (HPT), whereas few data have been published on its use in reoperations or in secondary and tertiary HPT. We report our initial experience with a rapid (12 min response) PTH immunochemiluminometric assay performed in the operating room during surgery in 12 patients with primary HPT, 16 end-stage renal disease patients with secondary HPT and five kidney transplanted subjects with tertiary HPT. Blood samples were taken at baseline, within 10 min after resection and subsequently at various intervals whenever needed. The mean PTH levels before and after parathyroidectomy were 230.5 pg/mL (range 69-842) and 47.3 pg/mL (range 5-184), respectively, in primary HPT, 855.0 pg/mL (416-1655) and 202.2 pg/mL (53-440) in secondary HPT, and 205.6 pg/mL (116-301) and 45.4 pg/mL (18-97) in tertiary HPT. All patients but one had a significant percentage decline from pre-excision values (mean 76.9%, 76.0%, and 76.1% in primary, secondary and tertiary HPT, respectively). While a reduction of more than 50% was observed in 30 out of 33 patients after the first intraoperative sampling, additional measurements were performed in 10 cases. On-site PTH monitoring with this user-friendly and reliable system has proved helpful in targeting PTH tests to give the surgeon a rapid and accurate assessment of the intervention. The development of optimal PTH sequence strategies with decision-focused analytical and clinical limits will improve the efficacy of "point-of-care" PTH assay and resource utilization.     

Mitochondrial Mutations in Subjects with Psychiatric Disorders

A considerable body of evidence supports the role of mitochondrial dysfunction in psychiatric disorders and mitochondrial DNA (mtDNA) mutations are known to alter brain energy metabolism, neurotransmission, and cause neurodegenerative disorders. Genetic studies focusing on common nuclear genome variants associated with these disorders have produced genome wide significant results but those studies have not directly studied mtDNA variants. The purpose of this study is to investigate, using next generation sequencing, the involvement of mtDNA variation in bipolar disorder, schizophrenia, major depressive disorder, and methamphetamine use. MtDNA extracted from multiple brain regions and blood were sequenced (121 mtDNA samples with an average of 8,800x coverage) and compared to an electronic database containing 26,850 mtDNA genomes. We confirmed novel and rare variants, and confirmed next generation sequencing error hotspots by traditional sequencing and genotyping methods. We observed a significant increase of non-synonymous mutations found in individuals with schizophrenia. Novel and rare non-synonymous mutations were found in psychiatric cases in mtDNA genes: ND6, ATP6, CYTB, and ND2. We also observed mtDNA heteroplasmy in brain at a locus previously associated with schizophrenia (T16519C). Large differences in heteroplasmy levels across brain regions within subjects suggest that somatic mutations accumulate differentially in brain regions. Finally, multiplasmy, a heteroplasmic measure of repeat length, was observed in brain from selective cases at a higher frequency than controls. These results offer support for increased rates of mtDNA substitutions in schizophrenia shown in our prior results. The variable levels of heteroplasmic/multiplasmic somatic mutations that occur in brain may be indicators of genetic instability in mtDNA.     

Recombinant protein production by large-scale transient gene expression in mammalian cells: state of the art and future perspectives

The expansion of the biologics pipeline depends on the identification of candidate proteins for clinical trials. Speed is one of the critical issues, and the rapid production of high quality, research-grade material for preclinical studies by transient gene expression (TGE) is addressing this factor in an impressive way: following DNA transfection, the production phase for TGE is usually 2-10 days. Recombinant proteins (r-proteins) produced by TGE can therefore enter the drug development and screening process in a very short time--weeks. With "classical" approaches to protein expression from mammalian cells, it takes months to establish a productive host cell line. This article summarizes efforts in industry and academia to use TGE to produce tens to hundreds of milligrams of r-proteins for either fundamental research or preclinical studies.     

Fibroblast growth factor-2 in hyperplastic pituitaries of D2R knockout female mice

Dopamine D2 receptor (D2R) knockout (KO) female mice develop chronic hyperprolactinemia and pituitary hyperplasia. Our objective was to study the expression of the mitogen fibroblast growth factor (FGF2) and its receptor, FGFR1, comparatively in pituitaries from KO and wild-type (WT) female mice. We also evaluated FGF2 subcellular localization and FGF2 effects on pituitary function. FGF2-induced prolactin release showed a similar response pattern in both genotypes, even though basal and FGF2-stimulated release was higher in KO. FGF2 stimulated pituitary cellular proliferation (MTS assay and [(3)H]thymidine incorporation), with no differences between genotypes. FGF2 concentration (measured by ELISA) in whole pituitaries or cultured cells was lower in KO (P < 0.00001 and 0.00014). Immunofluorescence histochemistry showed less FGF2 in pituitaries from KO females and revealed a distinct FGF2 localization pattern between genotypes, being predominantly nuclear in KO and cytosolic in WT pituitaries. Finally, FGF2 could not be detected in the conditioned media from pituitary cultures of both genotypes. FGFR1 levels (Western blot and immunohistochemistry) were higher in pituitaries of KO. Basal concentration of phosphorylated ERKs was lower in KO cells (P = 0.018). However, when stimulated with FGF2, a significantly higher increment of ERK phosphorylation was evidenced in KO cells (P < or = 0.02). We conclude that disruption of the D2R caused an overall decrease in pituitary FGF2 levels, with an increased distribution in the nucleus, and increased FGFR1 levels. These results are important in the search for reliable prognostic indicators for patients with pituitary dopamine-resistant prolactinomas, which will make tumor-specific therapy possible.     

Minimizing the overlap problem in protein NMR: a computational framework for precision amino acid labeling

MOTIVATION: Recent advances in cell-free protein expression systems allow specific labeling of proteins with amino acids containing stable isotopes ((15)N, (13) C and (2)H), an important feature for protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. Given this labeling ability, we present a mathematical optimization framework for designing a set of protein isotopomers, or labeling schedules, to reduce the congestion in the NMR spectra. The labeling schedules, which are derived by the optimization of a cost function, are tailored to a specific protein and NMR experiment. RESULTS: For 2D (15)N-(1)H HSQC experiments, we can produce an exact solution using a dynamic programming algorithm in under 2 h on a standard desktop machine. Applying the method to a standard benchmark protein, calmodulin, we are able to reduce the number of overlaps in the 500 MHz HSQC spectrum from 10 to 1 using four samples with a true cost function, and 10 to 4 if the cost function is derived from statistical estimates. On a set of 448 curated proteins from the BMRB database, we are able to reduce the relative percent congestion by 84.9% in their HSQC spectra using only four samples. Our method can be applied in a high-throughput manner on a proteomic scale using the server we developed. On a 100-node cluster, optimal schedules can be computed for every protein coded for in the human genome in less than a month. AVAILABILITY: A server for creating labeling schedules for (15)N-(1)H HSQC experiments as well as results for each of the individual 448 proteins used in the test set is available at http://nmr.proteomics.ics.uci.edu.     

Active promoters give rise to false positive ‘Phantom Peaks’ in ChIP-seq experiments

Chromatin immunoprecipitation (ChIP) is widely used to identify chromosomal binding sites. Chromatin proteins are cross-linked to their target sequences in living cells. The purified chromatin is sheared and the relevant protein is enriched by immunoprecipitation with specific antibodies. The co-purifying genomic DNA is then determined by massive parallel sequencing (ChIP-seq).We applied ChIP-seq to map the chromosomal binding sites for two ISWI-containing nucleosome remodeling factors, ACF and RSF, in Drosophila embryos. Employing several polyclonal and monoclonal antibodies directed against their signature subunits, ACF1 and RSF-1, robust profiles were obtained indicating that both remodelers co-occupied a large set of active promoters.Further validation included controls using chromatin of mutant embryos that do not express ACF1 or RSF-1. Surprisingly, the ChIP-seq profiles were unchanged, suggesting that they were not due to specific immunoprecipitation. Conservative analysis lists about 3000 chromosomal loci, mostly active promoters that are prone to non-specific enrichment in ChIP and appear as ‘Phantom Peaks’. These peaks are not obtained with pre-immune serum and are not prominent in input chromatin.Mining the modENCODE ChIP-seq profiles identifies potential Phantom Peaks in many profiles of epigenetic regulators. These profiles and other ChIP-seq data featuring prominent Phantom Peaks must be validated with chromatin from cells in which the protein of interest has been depleted.     

Investigation on the Origin of Sperm DNA Fragmentation: Role of Apoptosis,Immaturity and Oxidative Stress

Sperm DNA fragmentation (sDF) represents a threat to male fertility, human reproduction and the health of the offspring. The causes of sDF are still unclear, even if apoptosis, oxidative assault and defects in chromatin maturation are hypothesized. Using multicolor flow cytometry and sperm sorting, we challenged the three hypothesized mechanisms by simultaneously evaluating sDF and signs of oxidative damage (8-hydroxy, 2′-deoxyguanosine [8-OHdG] and malondialdehyde [MDA]), apoptosis (caspase activity and cleaved poly[ADP-ribose] polymerase [cPARP]) and sperm immaturity (creatine phosphokinase [CK] and excess of residual histones). Active caspases and c-PARP were concomitant with sDF in a high percentage of spermatozoa (82.6% ± 9.1% and 53.5% ± 16.4%, respectively). Excess of residual histones was significantly higher in DNA-fragmented sperm versus sperm without DNA fragmentation (74.8% ± 17.5% and 37.3% ± 16.6%, respectively, p < 0.005), and largely concomitant with active caspases. Conversely, oxidative damage was scarcely concomitant with sDF in the total sperm population, at variance with live sperm, where 8-OHdG and MDA were clearly associated to sDF. In addition, most live cells with active caspase also showed 8-OHdG, suggesting activation of apoptotic pathways in oxidative-injured live cells. This is the first investigation on the origin of sDF directly evaluating the simultaneous presence of the signs of the hypothesized mechanisms with DNA breaks at the single cell level. The results indicate that the main pathway leading to sperm DNA breaks is a process of apoptosis, likely triggered by an impairment of chromatin maturation in the testis and by oxidative stress during the transit in the male genital tract. These findings are highly relevant for clinical studies on the effects of drugs on sDF and oxidative stress in infertile men and for the development of new therapeutic strategies.     

A bias caused by ectopic development produces sexually dimorphic sperm in nematodes

Self-fertile hermaphrodites have evolved independently several times in the genus Caenorhabditis [1, 2]. These XX hermaphrodites make smaller sperm than males [3, 4], which they use to fertilize their own oocytes. Because larger sperm outcompete smaller sperm in nematodes [3-5], it had been assumed that this dimorphism evolved in response to sperm competition. However, we show that?it was instead caused by a developmental bias. When we transformed females of the species Caenorhabditis remanei into hermaphrodites [6], their sperm were significantly smaller than those of males. Because this species never makes hermaphrodites in the wild, this dimorphism cannot be due to selection. Instead, analyses of the related nematode Caenorhabditis elegans suggest that this dimorphism might reflect the development of sperm within the distinct physiological environment of the hermaphrodite gonad. These results reveal a new mechanism for some types of developmental bias-the effects of a novel physical location alter the development of ectopic cells in predictable ways.