A new family of CRISPR‐type V nucleases with C‐rich PAM recognition

Most CRISPR‐type V nucleases are stimulated to cleave double‐stranded (ds) DNA targets by a T‐rich PAM, which restricts their targeting range. Here, we identify and characterize a new family of type V RNA‐guided nuclease, Cas12l, that exclusively recognizes a C‐rich (5''‐CCY‐3′) PAM. The organization of genes within its CRISPR locus is similar to type II‐B CRISPR‐Cas9 systems, but both sequence analysis and functional studies establish it as a new family of type V effector. Biochemical experiments show that Cas12l nucleases function optimally between 37 and 52°C, depending on the ortholog, and preferentially cut supercoiled DNA. Like other type V nucleases, it exhibits collateral nonspecific ssDNA and ssRNA cleavage activity that is triggered by ssDNA or dsDNA target recognition. Finally, we show that one family member, Asp2Cas12l, functions in a heterologous cellular environment, altogether, suggesting that this new group of CRISPR‐associated nucleases may be harnessed as genome editing reagents.     

Bioremediation of Soil Contaminated with Diesel Using Inorganic Nitrogen Sources: Incorporating nth-Order Algorithm in the Evaluation of Process Kinetics

In the present study, we investigated the effects of inorganic nitrogen sources—(NPK fertilizer, 15:15:15), (urea fertilizer, 46:0:0), (NH₄)₂SO₄ as well as monitored natural attenuation on the bioremediation of diesel-polluted soil. At the end of the 6-week study, the highest degradation was recorded in soil amended with NPK fertilizer (95 ± 2.77%) while the least total petroleum hydrocarbon removal was observed in monitored natural attenuation (89 ± 2.91%). Nth-order kinetics effectively described three of the treatments out of the four treatment plans. These include urea amendment (r² = 0.9925, average relative error (ARE) = 1.45%, root mean square error (RMSE) = 0.038, k_n = (3.57 ± 0.61) × 10^?2, n = 1.33), NPK fertilizer amendment (r² = 0.9751, ARE = 3.241%, RMSE = 0.086, k_n = (8.04 ± 0.23) × 10^?1, n = 0.74), and monitored natural attenuation (r² = 0.9697, ARE = 2.77%, RMSE = 0.073, k_n = (1.57 ± 0.50) × 10^?2, n = 1.16). The values of n from the nth-order kinetics parameter estimation indicated that all the treatments resulted in diesel degradation that followed a first-order kinetics path. Thus, the outcome of kinetic modeling showed that nth-order can be used as validating tool when many kinetic orders are under consideration. The phytotoxicity assay with Zea mays showed that the treatments plans resulted in germination indices of 17–55%.     

Reversible oxidative modification as a mechanism for regulating retroviral protease dimerization and activation

Human immunodeficiency virus protease activity can be regulated by reversible oxidation of a sulfur-containing amino acid at the dimer interface. We show here that oxidation of this amino acid in human immunodeficiency virus type 1 protease prevents dimer formation. Moreover, we show that human T-cell leukemia virus type 1 protease can be similarly regulated through reversible glutathionylation of its two conserved cysteine residues. Based on the known three-dimensional structures and multiple sequence alignments of retroviral proteases, it is predicted that the majority of retroviral proteases have sulfur-containing amino acids at the dimer interface. The regulation of protease activity by the modification of a sulfur-containing amino acid at the dimer interface may be a conserved mechanism among the majority of retroviruses.     

Barrier passage and protein dynamics in enzymatically catalyzed reactions.

This review describes studies of particular enzymatically catalyzed reactions to investigate the possibility that catalysis is mediated by protein dynamics. That is, evolution has crafted the protein backbone of the enzyme to direct vibrations in such a fashion to speed reaction. The review presents the theoretical approach we have used to investigate this problem, but it is designed for the nonspecialist. The results show that in alcohol dehydrogenase, dynamic protein motion is in fact strongly coupled to chemical reaction in such a way as to promote catalysis. This result is in concert with both experimental data and interpretations for this and other enzyme systems studied in the laboratories of the two other investigators who have published reviews in this issue.     

More Powerful Likelihood Ratio Tests for Isotonic Binomial Proportions

Binomial group testing involves pooling individuals into groups and observing a binary response on each group. Results from the group tests can then be used to draw inference about population proportions. Its use as an experimental design has received much attention in recent years, especially in public‐health screening experiments and vector‐transfer designs in plant pathology. We investigate the benefits of group testing in situations wherein one desires to test whether or not probabilities are increasingly ordered across the levels of an observed qualitative covariate, i.e., across strata of a population or among treatment levels. We use a known likelihood ratio test for individual testing, but extend its use to group‐testing situations to show the increases in power conferred by using group testing when operating in this constrained parameter space. We apply our methods to data from an HIV study involving male subjects classified as intraveneous drug users.     

Modeling the impact of periodic bottlenecks, unidirectional mutation, and observational error in experimental evolution

Antibiotic resistant bacteria are a constant threat in the battle against infectious diseases. One strategy for reducing their effect is to temporarily discontinue the use of certain antibiotics in the hope that in the absence of the antibiotic the resistant strains will be replaced by the sensitive strains. An experiment where this strategy is employed in vitro [5] produces data which showed a slow accumulation of sensitive mutants. Here we propose a mathematical model and statistical analysis to explain this data.The stochastic model elucidates the trend and error structure of the data. It provides a guide for developing future sampling strategies, and provides a framework for long term predictions of the effects of discontinuing specific antibiotics on the dynamics of resistant bacterial populations.This Research is part of the Initiative in Bioinformatics and Evolutionary Studies (IBEST) at the University of Idaho. Funding was provided by NSF EPSCoR EPS-0080935, NSF EPSCoR, EPS-0132626, and NIH NCRR grant NIH NCRR- 20RR016448. Paul Joyce is also funded by NSF DEB-0089756, and NSF DMS-0072198.     

Empirical Bayesian estimation of the disease transmission probability in multiple-vector-transfer designs

Plant disease is responsible for major losses in agriculture throughout the world. Diseases are often spread by insect organisms that transmit a bacterium, virus, or other pathogen. To assess disease epidemics, plant pathologists often use multiple-vector-transfers. In such contexts, groups of insect vectors are moved from an infected source to each of n test plants that will then be observed for developing symptoms of infection. The purpose of this paper is to present new estimators for p, the probability of pathogen transmission for an individual vector, motivated from an empirical Bayesian approach. We specifically investigate four such estimators, characterize their small-sample properties, and propose new credible intervals for p. These estimators remove the need to specify hyperparameters a priori and are shown to be easier to compute than the classical Bayes estimators proposed by Chaubey and Li (1995, Journal of Official Statistics 11, 1035-1046) and Chick (1996, Biometrics 52, 1055-1062). Furthermore, some of these estimators are shown to have better frequentist properties than the commonly used maximum likelihood estimator and to provide a smaller Bayes risk than the estimator proposed by Burrows (1987, Phytopathology 77, 363-365).