Learning Context-Dependent DNA Mutation Patterns in Error-Prone Polymerase Chain Reaction.

We present a novel statistical learning method for studying context-dependent error rates in error-prone polymerase chain reaction (PCR) experiments. We demonstrate the method by applying it to error-prone PCR sequencing data and show how it may be exploited to improve the evolvability of genes in protein engineering.

De novo mutation rates at the single-mutation resolution in a human HBB gene region associated with adaptation and genetic disease.

Although it is known that the mutation rate varies across the genome, previous estimates were based on averaging across various numbers of positions. Here, we describe a method to measure the origination rates of target mutations at target base positions and apply it to a 6-bp region in the human hemoglobin subunit beta (HBB) gene and to the identical, paralogous hemoglobin subunit delta (HBD) region in sperm cells from both African and European donors. The HBB region of interest (ROI) includes the site of the hemoglobin S (HbS) mutation, which protects against malaria, is common in Africa, and has served as a classic example of adaptation by random mutation and natural selection. We found a significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than in Europeans in the HBB region studied. Finally, the rate of the 20A→T mutation, called the "HbS mutation" when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations; no instances were observed elsewhere. Further studies will be needed to examine mutation rates at the single-mutation resolution across these and other loci and organisms and to uncover the molecular mechanisms responsible.

Superior outcome of patients with favorable-risk acute myeloid leukemia using consolidation with autologous stem cell transplantation.

Autologous stem cell transplantation (ASCT), intensifying anti-leukemic effects without significant treatment-related mortality (TRM), is particularly appealing in AML with favorable genetic/molecular profile. This study retrospectively evaluated the outcomes of post-remission treatment in consecutive favorable-risk AML patients. Sixty-six patients were included: 32 had mutated NPM1/wild-type FLT-ITD, 16 had t(8:21) and 18 - inv(16). Forty patients received chemotherapy alone, 26 underwent ASCT upfront. In time-dependent analysis, the ASCT group demonstrated higher relapse-free (RFS) (p = .001) and overall survivals (OS) (p = .0007). The 1-year RFS and OS were 44.2% vs 88% and 71% vs 96% for chemotherapy and ASCT, respectively. The corresponding TRM was 4/40 (10.0%) and 0/26 (0%), with relapse rates of 70.0% and 19.2% (p = .0002). In multivariate analysis, ASCT was associated with superior OS and RFS. In conclusion, ASCT offers significantly superior RFS and OS in favorable-risk AML in first complete remission. These data support the recent resurgence of interest in ASCT for AML.

The Expression of Neuropilin-1 in Human Placentas From Normal and Preeclamptic Pregnancies.

Preeclampsia (PET) is a hypertensive disorder that affects 2% to 8% of pregnant women. Recent observations support the hypothesis that upregulation of placental anti-angiogenic factors are responsible for the clinical manifestations of the disease. Neuropilin-1 (NP-1) is a transmembrane protein that acts as a coreceptor for vascular endothelial growth factor and as a regulatory protein in the immune system. The aim of the study was to evaluate the expression of NP-1 in PET and normal placentas. Nineteen placental specimens from severe PET pregnancies were compared with 20 placental specimens of women with low-risk pregnancy. All the specimens underwent immunohistochemical staining with anti-human NP-1 antibody. The degree of NP-1 staining was measured both for intensity and extent. Our study demonstrated NP-1 immunoreactivity mainly in the decidual cells, the intermediate trophoblast, and the syncytiotrophoblast, particularly in the areas in the syncytial knots and shed particles. The particles were strongly NP-1 immunoreactive. The expression of NP-1 in the syncytiotrophoblast was lower in placentas of PET compared with control (P=0.017). Shedding of syncytiotrophoblast particles from placenta to maternal blood occurs in normal pregnancies and is enhanced during PET and contributes to the maternal vascular injury that characterizes PET. Our new observation that shows strong NP-1 immunoreactivity of these particles, and decreased NP1 expression in syncytiotrophoblast of PET placentas in comparison to the control group, may imply a role of NP-1 in PET.

Economical analysis of saturation mutagenesis experiments.

Saturation mutagenesis is a powerful technique for engineering proteins, metabolic pathways and genomes. In spite of its numerous applications, creating high-quality saturation mutagenesis libraries remains a challenge, as various experimental parameters influence in a complex manner the resulting diversity. We explore from the economical perspective various aspects of saturation mutagenesis library preparation: We introduce a cheaper and faster control for assessing library quality based on liquid media; analyze the role of primer purity and supplier in libraries with and without redundancy; compare library quality, yield, randomization efficiency, and annealing bias using traditional and emergent randomization schemes based on mixtures of mutagenic primers; and establish a methodology for choosing the most cost-effective randomization scheme given the screening costs and other experimental parameters. We show that by carefully considering these parameters, laboratory expenses can be significantly reduced.

Eye movements in chameleons are not truly independent - evidence from simultaneous monocular tracking of two targets.

Chameleons perform large-amplitude eye movements that are frequently referred to as independent, or disconjugate. When prey (an insect) is detected, the chameleon's eyes converge to view it binocularly and 'lock' in their sockets so that subsequent visual tracking is by head movements. However, the extent of the eyes' independence is unclear. For example, can a chameleon visually track two small targets simultaneously and monocularly, i.e. one with each eye? This is of special interest because eye movements in ectotherms and birds are frequently independent, with optic nerves that are fully decussated and intertectal connections that are not as developed as in mammals. Here, we demonstrate that chameleons presented with two small targets moving in opposite directions can perform simultaneous, smooth, monocular, visual tracking. To our knowledge, this is the first demonstration of such a capacity. The fine patterns of the eye movements in monocular tracking were composed of alternating, longer, 'smooth' phases and abrupt 'step' events, similar to smooth pursuits and saccades. Monocular tracking differed significantly from binocular tracking with respect to both 'smooth' phases and 'step' events. We suggest that in chameleons, eye movements are not simply 'independent'. Rather, at the gross level, eye movements are (i) disconjugate during scanning, (ii) conjugate during binocular tracking and (iii) disconjugate, but coordinated, during monocular tracking. At the fine level, eye movements are disconjugate in all cases. These results support the view that in vertebrates, basic monocular control is under a higher level of regulation that dictates the eyes' level of coordination according to context.

Semaphorin 3A: an immunoregulator in systemic sclerosis.

ABSTARCT: Semaphorin 3A (sema3A) plays a regulatory role in immune responses, mainly affecting the activation of regulatory T cells. It has been found to correlate with disease activity in rheumatoid arthritis and systemic lupus erythematosus (SLE). To investigate the expression of sema3A in patients with systemic sclerosis (SSc) compared to healthy controls and SLE disease controls and to correlate it with clinical characteristics, 27 SSc patients, 42 SLE patients and 28 healthy controls were enrolled. Serum level of sema3A was measured by ELISA, and expression of sema3A on regulatory T cells was evaluated by FACS analysis. SSc patients were evaluated for demographics, clinical manifestations, routine laboratory results, nailfold videocapillaroscopy, pulmonary function tests, echocardiograms, modified Rodnan skin score, and disease activity and severity scores. Serum levels of semaphorin 3A were lower in SSc compared to healthy controls 14.38 ± 5.7 versus 27.14 ± 8.4 ng/ml, p < 0.0001 and similar to SLE 15.7 ± 4.3 ng/ml. The expression of semaphorin 3A on regulatory T cells was also lower in SSc compared to healthy controls 61.7 ± 15.7 versus 88.7 ± 3. 7 % (p < 0.0001). Semaphorin 3A serum level inversely correlated with the duration of disease: r = -0.4, p = 0.036 and with low C4 level r = 0.66, p = 0.026. SCL-70 antibody positivity was associated with a lower semaphorin 3A level (difference in mean of 3.44, p = 0.06). Sema3A expression is low in SSc serum and more specifically on regulatory T cells. This may help explain the reduced activation of regulatory T cells in SSc.

Probabilistic methods in directed evolution: library size, mutation rate, and diversity.

Directed evolution has emerged as an important tool for engineering proteins with improved or novel properties. Because of their inherent reliance on randomness, directed evolution protocols are amenable to probabilistic modeling and analysis. This chapter summarizes and reviews in a nonmathematical way some of the probabilistic works related to directed evolution, with particular focus on three of the most widely used methods: saturation mutagenesis, error-prone PCR, and in vitro recombination. The ultimate aim is to provide the reader with practical information to guide the planning and design of directed evolution studies. Importantly, the applications and locations of freely available computational resources to assist with this process are described in detail.

Brief report: lysyl oxidase is a potential biomarker of fibrosis in systemic sclerosis.

OBJECTIVE: Fibrosis is a major cause of morbidity and mortality in systemic sclerosis (SSc). Levels of lysyl oxidase (LOX), an extracellular enzyme that stabilizes collagen fibrils, have been found to be elevated in the skin of SSc patients, but have not been evaluated in the serum or correlated with the clinical parameters. We undertook this study to evaluate serum LOX levels in SSc patients and to correlate these levels with clinical parameters of SSc. METHODS: SSc patients were evaluated for demographic features, clinical manifestations, routine laboratory tests, serum autoantibodies, serum LOX concentrations, and nailfold capillaroscopy patterns. They underwent pulmonary function testing, echocardiography, and high-resolution computed tomography scans of the lung, assessment of skin fibrosis by the modified Rodnan skin thickness score (MRSS), and assessment of disease severity and activity by the Medsger severity scale and the Valentini activity index. RESULTS: Twenty-six SSc patients were evaluated and compared with 25 healthy controls and with 9 disease control patients with primary myelofibrosis. Almost 62% of the SSc patients (16 of 26) had limited cutaneous SSc (lcSSc), while 38% had diffuse cutaneous SSc (dcSSc) (10 of 26); 31% of the patients (8 of 26) had lung involvement. The LOX concentration in SSc patients was higher than that in healthy controls and similar to that in disease controls (P < 0.0001), and it was significantly higher in patients with dcSSc than in those with lcSSc (P = 0.006). The LOX concentration correlated with the MRSS in patients without lung fibrosis. CONCLUSION: This study is the first to demonstrate high serum LOX levels in SSc patients that correlate specifically with skin fibrosis. These correlations suggest that LOX levels may serve as a novel biomarker of fibrosis. Future studies are warranted to determine whether LOX is a potential therapeutic target in SSc.

Optimal scanning of all single-point mutants of a protein.

In protein engineering, useful information may be gained from systematically generating and screening all single-point mutants of a given protein. We model and analyze an iterative two-stage procedure to generate all these mutants. At each position, L variants are generated in the first stage via saturation mutagenesis and are sequenced. In the second stage, the missing variants (out of the 19 possible single-point substitutions) are produced via site-directed mutagenesis. We study the economic tradeoff associated with varying L, and derive its optimal value given the experimental parameters.

Fitness loss and library size determination in saturation mutagenesis.

Saturation mutagenesis is a widely used directed evolution technique, in which a large number of protein variants, each having random amino acids in certain predetermined positions, are screened in order to discover high-fitness variants among them. Several metrics for determining the library size (the number of variants screened) have been suggested in the literature, but none of them incorporates the actual fitness of the variants discovered in the experiment. We present the results of an extensive simulation study, which is based on probabilistic models for protein fitness landscape, and which investigates how the result of a saturation mutagenesis experiment--the fitness of the best variant discovered--varies as a function of the library size. In particular, we study the loss of fitness in the experiment: the difference between the fitness of the best variant discovered, and the fitness of the best variant in variant space. Our results are that the existing criteria for determining the library size are conservative, so smaller libraries are often satisfactory. Reducing the library size can save labor, time, and expenses in the laboratory.

Optimal codon randomization via mathematical programming.

Codon randomization via degenerate oligonucleotides is a widely used approach for generating protein libraries. We use integer programming methodology to model and solve the problem of computing the minimal mixture of oligonucleotides required to induce an arbitrary target probability over the 20 standard amino acids. We consider both randomization via conventional degenerate oligonucleotides, which incorporate at each position of the randomized codon certain nucleotides in equal probabilities, and randomization via spiked oligonucleotides, which admit arbitrary nucleotide distribution at each of the codon's positions. Existing methods for computing such mixtures rely on various heuristics.

Wilms' tumor gene 1: a possible new proangiogenic factor in Hodgkin lymphoma.

INTRODUCTION: Wilms' tumor gene 1 (WT1) was recently found to play a role in solid and hematologic malignancies and serves as a marker of prognosis and minimal residual disease in acute leukemia. WT1 was also found to be involved in tumor angiogenesis. There are no data concerning the involvement of WT1 in angiogenesis in lymphoproliferative tumors. The aim of this study was to explore the involvement of WT1 in Hodgkin lymphoma. METHODS: The expression of WT1, neuropilin 1, and VEGF was tested by immunohistochemistry in lymph nodes biopsies of 20 Hodgkin patients and 7 reactive lymph nodes. RESULTS: WT1 was expressed in endothelial cells, in 95% of the malignant lymph nodes. The average of WT1 expression scale was higher in the malignant lymph nodes than in reactive lymph nodes. We found a positive correlation between WT1 expression scale and the angiogenesis scale (0.53) that was statistically significant (P<0.05). As the number of vessels increases, the expression of WT1 is more intense. CONCLUSIONS: We found, for the first time, that WT1 is expressed in endothelial cells in Hodgkin lymphoma. The clinical implications of these findings should be tested in a future study.

When second best is good enough: another probabilistic look at saturation mutagenesis.

We developed new criteria for determining the library size in a saturation mutagenesis experiment. When the number of all possible distinct variants is large, any of the top-performing variants (e.g., any of the top three) is likely to meet the design requirements, so the probability that the library contains at least one of them is a sensible criterion for determining the library size. By using a criterion of this type, one may significantly reduce the library size and thus save costs and labor while minimally compromising the quality of the best variant discovered. We present the probabilistic tools underlying these criteria and use them to compare the efficiencies of four randomization schemes: NNN, which uses all 64 codons; NNB, which uses 48 codons; NNK, which uses 32 codons; and MAX, which assigns equal probabilities to each of the 20 amino acids. MAX was found to be the most efficient randomization scheme and NNN the least efficient. TopLib, a computer program for carrying out the related calculations, is available through a user-friendly Web server.

Improving biocatalyst performance by integrating statistical methods into protein engineering.

Directed evolution and rational design were used to generate active variants of toluene-4-monooxygenase (T4MO) on 2-phenylethanol (PEA), with the aim of producing hydroxytyrosol, a potent antioxidant. Due to the complexity of the enzymatic system-four proteins encoded by six genes-mutagenesis is labor-intensive and time-consuming. Therefore, the statistical model of Nov and Wein (J. Comput. Biol. 12:247-282) was used to reduce the number of variants produced and evaluated in a lab. From an initial data set of 24 variants, with mutations at nine positions, seven double or triple mutants were identified through statistical analysis. The average activity of these mutants was 4.6-fold higher than the average activity of the initial data set. In an attempt to further improve the enzyme activity to obtain PEA hydroxylation, a second round of statistical analysis was performed. Nine variants were considered, with 3, 4, and 5 point mutations. The average activity of the variants obtained in the second statistical round was 1.6-fold higher than in the first round and 7.3-fold higher than that of the initial data set. The best variant discovered, TmoA I100A E214G D285Q, exhibited an initial oxidation rate of 4.4 ± 0.3 nmol/min/mg protein, which is 190-fold higher than the rate obtained by the wild type. This rate was also 2.6-fold higher than the activity of the wild type on the natural substrate toluene. By considering only 16 preselected mutants (out of ∼13,000 possible combinations), a highly active variant was discovered with minimum time and effort.

FragBag, an accurate representation of protein structure, retrieves structural neighbors from the entire PDB quickly and accurately.

Fast identification of protein structures that are similar to a specified query structure in the entire Protein Data Bank (PDB) is fundamental in structure and function prediction. We present FragBag: An ultrafast and accurate method for comparing protein structures. We describe a protein structure by the collection of its overlapping short contiguous backbone segments, and discretize this set using a library of fragments. Then, we succinctly represent the protein as a "bags-of-fragments"-a vector that counts the number of occurrences of each fragment-and measure the similarity between two structures by the similarity between their vectors. Our representation has two additional benefits: (i) it can be used to construct an inverted index, for implementing a fast structural search engine of the entire PDB, and (ii) one can specify a structure as a collection of substructures, without combining them into a single structure; this is valuable for structure prediction, when there are reliable predictions only of parts of the protein. We use receiver operating characteristic curve analysis to quantify the success of FragBag in identifying neighbor candidate sets in a dataset of over 2,900 structures. The gold standard is the set of neighbors found by six state of the art structural aligners. Our best FragBag library finds more accurate candidate sets than the three other filter methods: The SGM, PRIDE, and a method by Zotenko et al. More interestingly, FragBag performs on a par with the computationally expensive, yet highly trusted structural aligners STRUCTAL and CE.

Minimum-norm estimation for binormal receiver operating characteristic (ROC) curves.

The receiver operating characteristic (ROC) curve is often used to assess the usefulness of a diagnostic test. We present a new method to estimate the parameters of a popular semi-parametric ROC model, called the binormal model. Our method is based on minimization of the functional distance between two estimators of an unknown transformation postulated by the model, and has a simple, closed-form solution. We study the asymptotics of our estimators, show via simulation that they compare favorably with existing estimators, and illustrate how covariates may be incorporated into the norm minimization framework.

Enzyme improvement in the absence of structural knowledge: a novel statistical approach.

Most existing methods for improving protein activity are laborious and costly, as they either require knowledge of protein structure or involve expression and screening of a vast number of protein mutants. We describe here a successful first application of a novel approach, which requires no structural knowledge and is shown to significantly reduce the number of mutants that need to be screened. In the first phase of this study, around 7000 mutants were screened through standard directed evolution, yielding a 230-fold improvement in activity relative to the wild type. Using sequence analysis and site-directed mutagenesis, an additional single mutant was then produced, with 500-fold improved activity. In the second phase, a novel statistical method for protein improvement was used; building on data from the first phase, only 11 targeted additional mutants were produced through site-directed mutagenesis, and the best among them achieved a >1500-fold improvement in activity over the wild type. Thus, the statistical model underlying the experiment was validated, and its predictions were shown to reduce laboratory labor and resources.

Modeling and analysis of protein design under resource constraints.

The potency, or fitness, of a protein-based drug can be enhanced by changing the sequence of its underlying protein. We present a novel stochastic model for the sequence-fitness relation, and estimate its four parameters from industrial data. Using this model, we formulate and analyze two variants of the protein design problem. In the single-period design problem, the designer needs to decide under capacity constraints which set of sequences to screen in order to maximize the expected fitness of the best sequence in the set. In the more general two-period design problem, the designer can afford two screening rounds and needs to allocate resources optimally across the two periods to maximize the same objective function. Analytical and simulation results allow us to assess the utility of the proposed design strategies for various parameter regimes.