KREX2 Is Not Essential for Either Procyclic or Bloodstream Form Trypanosoma brucei

Background: Most mitochondrial mRNAs in Trypanosoma brucei require RNA editing for maturation and translation. The edited RNAs primarily encode proteins of the oxidative phosphorylation system. These parasites undergo extensive changes in energy metabolism between the insect and bloodstream stages which are mirrored by alterations in RNA editing. Two U-specific exonucleases, KREX1 and KREX2, are both present in protein complexes (editosomes) that catalyze RNA editing but the relative roles of each protein are not known. Methodology/Principal Findings: The requirement for KREX2 for RNA editing in vivo was assessed in both procyclic (insect) and bloodstream form parasites by methods that use homologous recombination for gene elimination. These studies resulted in null mutant cells in which both alleles were eliminated. The viability of these cells demonstrates that KREX2 is not essential in either life cycle stage, despite certain defects in RNA editing in vivo. Furthermore, editosomes isolated from KREX2 null cells require KREX1 for in vitro U-specific exonuclease activity. Conclusions: KREX2 is a U-specific exonuclease that is dispensable for RNA editing in vivo in T. brucei BFs and PFs. This result suggests that the U deletion activity, which is required for RNA editing, is primarily mediated in vivo by KREX1 which is normally found associated with only one type of editosome. The retention of the KREX2 gene implies a non-essential role o

Editosome Accessory Factors KREPB9 and KREPB10 in Trypanosoma brucei

Multiprotein complexes, called editosomes, catalyze the uridine insertion and deletion RNA editing that forms translatable mitochondrial mRNAs in kinetoplastid parasites. We have identified here two new U1-like zinc finger proteins that associate with editosomes and have shown that they are related to KREPB6, KREPB7, and KREPB8, and thus we have named them Kinetoplastid RNA Editing Proteins, KREPB9 and KREPB10. They are conserved and syntenic in trypanosomatids although KREPB10 is absent in Trypanosoma vivax and both are absent in Leishmania. Tandem affinity purification (TAP)-tagged KREPB9 and KREPB10 incorporate into ∼20S editosomes and/or subcomplexes thereof and preferentially associate with deletion subcomplexes, as do KREPB6, KREPB7, and KREPB8. KREPB10 also associates with editosomes that are isolated via a chimeric endonuclease, KREN1 in KREPB8 RNA interference (RNAi) cells, or MEAT1. The purified complexes have precleaved editing activities and endonuclease cleavage activity that appears to leave a 5′ OH on the 3′ product. RNAi knockdowns did not affect growth but resulted in relative reductions of both edited and unedited mitochondrial mRNAs. The similarity of KREPB9 and KREPB10 to KREPB6, KREPB7, and KREPB8 suggests they may be accessory factors that affect editing endonuclease activity and as a consequence may affect mitochondrial mRNA stability. KREPB9 and KREPB10, along with KREPB6, KREPB7, and KREPB8, may enable the endonucleases to discriminate among and accurately cleave hundreds of different editing sites and may be involved in the control of differential editing during the life cycle of T. brucei

Artificial Intelligence and the Disruption of Higher Education: Strategies for Integrations across Disciplines

Artificial intelligence (AI) and its impact on society have received a great deal of attention in the past five years since the first Stanford AI100 report. AI already globally impacts individuals in critical and personal ways, and many industries will continue to experience disruptions as the full algorithmic effects are understood. Higher education is one of the industries that will be greatly impacted; consequently, many institutions have begun accelerating its adoption across disciplines to address the fast-approaching market shift. Recent advances with the technology are especially promising for its potential to create and scale personalized learning for students, to optimize strategies for learning outcomes, and to increase access to a more diverse populations. In the US alone, colleges are predicted to witness a 48% growth in AI market between 2018-2022. Research has confirmed that the current use of AI in education (AIEd) leads to positive outcomes, including improved learning outcomes for students, along with increased access, increased retention, lower cost of education, and decreased time to completion. Future uses of AI will include the following: enabling engaging and interactive education anytime and anywhere; personalized AI mentors that will help students identify and reach their goals; and mass-personalization that will allow AI to be tailored to each student’s learning style, level, and needs. Yet with all the potential benefits that AI and machine learning (ML) may provide students, there remains a general reticence to adopt this technology because of misconceptions and perceptions that faculty will need to retool since their current teaching strategies will be outmoded. This study provides an overview for those in higher education of what AI is and is not, and how it may be used in various disciplines. Considerations of becoming an AI institution include the following: 1) curricular planning and oversight from academic affairs to identify appropriate use cases for AI in various disciplines, and 2) coordination with IT and technology infrastructure to develop ML to support student services in general

PyCogent: a toolkit for making sense from sequence

The COmparative GENomic Toolkit, a framework for probabilistic analyses of biological sequences, devising workflows and generating publication quality graphics, has been implemented in Python

Lexis and grammar of mitochondrial RNA processing in Trypanosomes

Trypanosoma brucei spp. cause African human and animal trypanosomiasis, a burden on health and economy in Africa. These hemoflagellates are distinguished by a kinetoplast nucleoid containing mitochondrial DNAs of two kinds: maxicircles encoding ribosomal RNAs (rRNAs) and proteins and minicircles bearing guide RNAs (gRNAs) for mRNA editing. All RNAs are produced by a phage-type RNA polymerase as 3' extended precursors, which undergo exonucleolytic trimming. Most pre-mRNAs proceed through 3' adenylation, uridine insertion/deletion editing, and 3' A/U-tailing. The rRNAs and gRNAs are 3' uridylated. Historically, RNA editing has attracted major research effort, and recently essential pre- and postediting processing events have been discovered. Here, we classify the key players that transform primary transcripts into mature molecules and regulate their function and turnover

Whole blood transcriptome changes following controlled human malaria infection in malaria pre-exposed volunteers correlate with parasite prepatent period

Malaria continues to be one of mankind's most devastating diseases despite the many and varied efforts to combat it. Indispensable for malaria elimination and eventual eradication is the development of effective vaccines. Controlled human malaria infection (CHMI) is an invaluable tool for vaccine efficacy assessment and investigation of early immunological and molecular responses against Plasmodium falciparum infection. Here, we investigated gene expression changes following CHMI using RNA-Seq. Peripheral blood samples were collected in Bagamoyo, Tanzania, from ten adults who were injected intradermally (ID) with 2.5x104 aseptic, purified, cryopreserved P. falciparum sporozoites (Sanaria® PfSPZ Challenge). A total of 2,758 genes were identified as differentially expressed following CHMI. Transcriptional changes were most pronounced on day 5 after inoculation, during the clinically silent liver phase. A secondary analysis, grouping the volunteers according to their prepatent period duration, identified 265 genes whose expression levels were linked to time of blood stage parasitemia detection. Gene modules associated with these 265 genes were linked to regulation of transcription, cell cycle, phosphatidylinositol signaling and erythrocyte development. Our study showed that in malaria pre-exposed volunteers, parasite prepatent period in each individual is linked to magnitude and timing of early gene expression changes after ID CHMI

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks

A search is presented for narrow heavy resonances X decaying into pairs of Higgs bosons (H) in proton-proton collisions collected by the CMS experiment at the LHC at root s = 8 TeV. The data correspond to an integrated luminosity of 19.7 fb(-1). The search considers HH resonances with masses between 1 and 3 TeV, having final states of two b quark pairs. Each Higgs boson is produced with large momentum, and the hadronization products of the pair of b quarks can usually be reconstructed as single large jets. The background from multijet and t (t) over bar events is significantly reduced by applying requirements related to the flavor of the jet, its mass, and its substructure. The signal would be identified as a peak on top of the dijet invariant mass spectrum of the remaining background events. No evidence is observed for such a signal. Upper limits obtained at 95 confidence level for the product of the production cross section and branching fraction sigma(gg -> X) B(X -> HH -> b (b) over barb (b) over bar) range from 10 to 1.5 fb for the mass of X from 1.15 to 2.0 TeV, significantly extending previous searches. For a warped extra dimension theory with amass scale Lambda(R) = 1 TeV, the data exclude radion scalar masses between 1.15 and 1.55 TeV

Measurement of the Splitting Function in &ITpp &ITand Pb-Pb Collisions at root&ITsNN&IT=5.02 TeV

Data from heavy ion collisions suggest that the evolution of a parton shower is modified by interactions with the color charges in the dense partonic medium created in these collisions, but it is not known where in the shower evolution the modifications occur. The momentum ratio of the two leading partons, resolved as subjets, provides information about the parton shower evolution. This substructure observable, known as the splitting function, reflects the process of a parton splitting into two other partons and has been measured for jets with transverse momentum between 140 and 500 GeV, in pp and PbPb collisions at a center-of-mass energy of 5.02 TeV per nucleon pair. In central PbPb collisions, the splitting function indicates a more unbalanced momentum ratio, compared to peripheral PbPb and pp collisions.. The measurements are compared to various predictions from event generators and analytical calculations.Peer reviewe