Computational Modelling of Genome-Side Transcription Assembly Networks Using a Fluidics Analogy

Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets

Evolution of reproductive development in the volvocine algae

The evolution of multicellularity, the separation of germline cells from sterile somatic cells, and the generation of a male–female dichotomy are certainly among the greatest innovations of eukaryotes. Remarkably, phylogenetic analysis suggests that the shift from simple to complex, differentiated multicellularity was not a unique progression in the evolution of life, but in fact a quite frequent event. The spheroidal green alga Volvox and its close relatives, the volvocine algae, span the full range of organizational complexity, from unicellular and colonial genera to multicellular genera with a full germ–soma division of labor and male–female dichotomy; thus, these algae are ideal model organisms for addressing fundamental issues related to the transition to multicellularity and for discovering universal rules that characterize this transition. Of all living species, Volvox carteri represents the simplest version of an immortal germline producing specialized somatic cells. This cellular specialization involved the emergence of mortality and the production of the first dead ancestors in the evolution of this lineage. Volvocine algae therefore exemplify the evolution of cellular cooperation from cellular autonomy. They also serve as a prime example of the evolution of complex traits by a few successive, small steps. Thus, we learn from volvocine algae that the evolutionary transition to complex, multicellular life is probably much easier to achieve than is commonly believed

Stable nuclear transformation of Eudorina elegans

Lerche K, Hallmann A. Stable nuclear transformation of Eudorina elegans. BMC Biotechnology. 2013;13(1): 11.UNLABELLED: ABSTRACT: BACKGROUND: A fundamental step in evolution was the transition from unicellular to differentiated, multicellular organisms. Volvocine algae have been used for several decades as a model lineage to investigate the evolutionary aspects of multicellularity and cellular differentiation. There are two well-studied volvocine species, a unicellular alga (Chlamydomonas reinhardtii) and a multicellular alga with differentiated cell types (Volvox carteri). Species with intermediate characteristics also exist, which blur the boundaries between unicellularity and differentiated multicellularity. These species include the globular alga Eudorina elegans, which is composed of 16-32 cells. However, detailed molecular analyses of E. elegans require genetic manipulation. Unfortunately, genetic engineering has not yet been established for Eudorina, and only limited DNA and/or protein sequence information is available. RESULTS: Here, we describe the stable nuclear transformation of E. elegans by particle bombardment using both a chimeric selectable marker and reporter genes from different heterologous sources. Transgenic algae resistant to paromomycin were achieved using the aminoglycoside 3'-phosphotransferase VIII (aphVIII) gene of Streptomyces rimosus, an actinobacterium, under the control of an artificial promoter consisting of two V. carteri promoters in tandem. Transformants exhibited an increase in resistance to paromomycin by up to 333-fold. Co-transformation with non-selectable plasmids was achieved with a rate of 50 - 100%. The luciferase (gluc) gene from the marine copepod Gaussia princeps, which previously was engineered to match the codon usage of C. reinhardtii, was used as a reporter gene. The expression of gluc was mediated by promoters from C. reinhardtii and V. carteri. Heterologous heat shock promoters induced an increase in luciferase activity (up to 600-fold) at elevated temperatures. Long-term stability and both constitutive and inducible expression of the co-bombarded gluc gene was demonstrated by transcription analysis and bioluminescence assays. CONCLUSIONS: Heterologous flanking sequences, including promoters, work in E. elegans and permit both constitutive and inducible expression of heterologous genes. Stable nuclear transformation of E. elegans is now routine. Thus, we show that genetic engineering of a species is possible even without the resources of endogenous genes and promoters

Molecular architecture of axonemal microtubule doublets revealed by cryo-electron tomography

The axoneme, which forms the core of eukaryotic flagella and cilia, is one of the largest macromolecular machines with a structure that is largely conserved from protists to mammals. Microtubule doublets are structural components of axonemes containing a number of proteins besides tubulin, and are usually found in arrays of nine doublets arranged around two singlet microtubules. Coordinated sliding of adjacent doublets, which involves a host of other proteins in the axoneme, produces periodic beating movements of the axoneme. We have obtained a 3D density map of intact microtubule doublets using cryo-electron tomography and image averaging. Our map, with a resolution of about 3 nm, provides insights into locations of particular proteins within the doublets and the structural features of the doublets that define their mechanical properties. We identify likely candidates for several of these non-tubulin components of the doublets. This work offers novel insight on how tubulin protofilaments and accessory proteins attach together to form the doublets and provides a structural basis for understanding doublet function in axonemes

A Guided Tour of Artificial Intelligence Research - Volume III: Interfaces and Applications of Artificial Intelligence

International audienceEn 3 volumes : https://www.springer.com/gp/book/9783030061630 (vol.1) et https://www.springer.com/gp/book/9783030061661 (vol. 2) et https://www.springer.com/gp/book/9783030061692 (vol.3). The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). Implementing reasoning or decision making processes requires an appropriate representation of the pieces of information to be exploited. This first volume starts with a historical chapter sketching the slow emergence of building blocks of AI along centuries. Then the volume provides an organized overview of different logical, numerical, or graphical representation formalisms able to handle incomplete information, rules having exceptions, probabilistic and possibilistic uncertainty (and beyond), as well as taxonomies, time, space, preferences, norms, causality, and even trust and emotions among agents. Different types of reasoning, beyond classical deduction, are surveyed including nonmonotonic reasoning, belief revision, updating, information fusion, reasoning based on similarity (case-based, interpolative, or analogical), as well as reasoning about actions, reasoning about ontologies (description logics), argumentation, and negotiation or persuasion between agents. Three chapters deal with decision making, be it multiple criteria, collective, or under uncertainty. Two chapters cover statistical computational learning and reinforcement learning (other machine learning topics are covered in Volume 2). Chapters on diagnosis and supervision, validation and explanation, and knowledge base acquisition complete the volume