In this study, we present a novel methodology to infer indel parameters from multiple sequence alignments (MSAs) based on simulations. Our algorithm searches for the set of evolutionary parameters describing indel dynamics which best fits a given input MSA. In each step of the search, we use parametric bootstraps and the Mahalanobis distance to estimate how well a proposed set of parameters fits input data. Using simulations, we demonstrate that our methodology can accurately infer the indel parameters for a large variety of plausible settings. Moreover, using our methodology, we show that indel parameters substantially vary between three genomic data sets: Mammals, bacteria, and retroviruses. Finally, we demonstrate how our methodology can be used to simulate MSAs based on indel parameters inferred from real data sets.
MicroRNAs (miRNAs) regulate gene output by targeting degenerate elements in mRNAs and have undergone drastic expansions in higher metazoan genomes. The evolutionary advantage of maintaining copies of highly similar miRNAs is not well understood, nor is it clear what unique functions, if any, miRNA family members possess. Here, we study evolutionary patterns of metazoan miRNAs, focusing on the targeting preferences of the let-7 and miR-10 families. These studies reveal hotspots for sequence evolution with implications for targeting and secondary structure. High-throughput screening for functional targets reveals that each miRNA represses sites with distinct features and regulates a large number of genes with cooperative function in regulatory networks. Unexpectedly, given the high degree of similarity, single-nucleotide changes grant miRNA family members with distinct targeting preferences. Together, our data suggest complex functional relationships among miRNA duplications, novel expression patterns, sequence change, and the acquisition of new targets.
Mathematical models of infectious diseases are a valuable tool in understanding the mechanisms and patterns of disease transmission. It is, however, a difficult subject to teach, requiring both mathematical expertise and extensive subject-matter knowledge of a variety of disease systems. In this article, we explore several uses of zombie epidemics to make mathematical modeling and infectious disease epidemiology more accessible to public health professionals, students, and the general public. We further introduce a web-based simulation, White Zed (http://cartwrig.ht/apps/whitezed/), that can be deployed in classrooms to allow students to explore models before implementing them. In our experience, zombie epidemics are familiar, approachable, flexible, and an ideal way to introduce basic concepts of infectious disease epidemiology.
Time-resolved fluorescence spectroscopy was used to explore the pathway and kinetics of energy transfer in photosynthetic membrane vesicles (chromatophores) isolated from Rhodobacter (Rba.) sphaeroides cells harvested 2, 4, 6 or 24 hours after a transition from growth in high to low level illumination. As previously observed, this light intensity transition initiates the remodeling of the photosynthetic apparatus and an increase in the number of light harvesting 2 (LH2) complexes relative to light harvesting 1 (LH1) and reaction center (RC) complexes. It has generally been thought that the increase in LH2 complexes served the purpose of increasing the overall energy transmission to the RC. However, fluorescence lifetime measurements and analysis in terms of energy transfer within LH2 and between LH2 and LH1 indicate that, during the remodeling time period measured, only a portion of the additional LH2 generated are well connected to LH1 and the reaction center. The majority of the additional LH2 fluorescence decays with a lifetime comparable to that of free, unconnected LH2 complexes. The presence of large LH2-only domains has been observed by atomic force microscopy in Rba. sphaeroides chromatophores (Bahatyrova et al., Nature, 2004, 430, 1058), providing structural support for the existence of pools of partially connected LH2 complexes. These LH2-only domains represent the light-responsive antenna complement formed after a switch in growth conditions from high to low illumination, while the remaining LH2 complexes occupy membrane regions containing mixtures of LH2 and LH1–RC core complexes. The current study utilized a multi-parameter approach to explore the fluorescence spectroscopic properties related to the remodeling process, shedding light on the structure-function relationship of the photosynthetic assembles. Possible reasons for the accumulation of these largely disconnected LH2-only pools are discussed.
Recent transcriptome data from yeast, worm, plants, and humans has shown that alternative polyadenylation (APA), a mechanism that enables expression of multiple 3′UTR isoforms for the same gene, is widespread in eukaryotic organisms. It is still poorly understood why metazoans require multiple 3′UTRs for the same gene, but accumulating evidence suggests that APA is largely regulated at a tissue-specific level. APA may direct combinatorial variation between cis-elements and microRNAs, perhaps to regulate gene expression in a tissue-specific manner. Apart from a few single gene anecdotes, this idea has not been systematically explored.
This dissertation research employs a systems biology approach to study the somatic tissue dynamics of APA and its impact on microRNA targeting networks in the small nematode C. elegans. In the first aim, tools were developed and applied to isolate and sequence mRNA from worm intestine and muscle tissues, which revealed pervasive tissue-specific APA correlated with microRNA regulation. The second aim provides genetic evidence that two worm genes use APA to escape repression by microRNAs in the body muscle. Finally, in aim three, mRNA from five additional somatic worm tissues was sequenced and their 3′ends mapped, allowing for an integrative study of APA and microRNA targeting dynamics in worms. Together, this work provides evidence that APA is a pervasive mechanism operating in somatic tissues of C. elegans with the potential to significantly rearrange their microRNA regulatory networks and precisely dose their gene expression.
Background: Chemistry and particularly enzymology at surfaces is a topic of rapidly growing interest, both in terms of its role in biological systems and its application in biocatalysis. Existing protein immobilization approaches, including noncovalent or covalent attachments to solid supports, have difficulties in controlling protein orientation, reducing nonspecific absorption and preventing protein denaturation. New strategies for enzyme immobilization are needed that allow the precise control over orientation and position and thereby provide optimized activity.
Methodology/Principal Findings: A method is presented for utilizing peptide ligands to immobilize enzymes on surfaces with improved enzyme activity and stability. The appropriate peptide ligands have been rapidly selected from high-density arrays and when desirable, the peptide sequences were further optimized by single-point variant screening to enhance both the affinity and activity of the bound enzyme. For proof of concept, the peptides that bound to β-galactosidase and optimized its activity were covalently attached to surfaces for the purpose of capturing target enzymes. Compared to conventional methods, enzymes immobilized on peptide-modified surfaces exhibited higher specific activity and stability, as well as controlled protein orientation.
Conclusions/Significance: A simple method for immobilizing enzymes through specific interactions with peptides anchored on surfaces has been developed. This approach will be applicable to the immobilization of a wide variety of enzymes on surfaces with optimized orientation, location and performance, and provides a potential mechanism for the patterned self-assembly of multiple enzymes on surfaces.