Open problems in artificial life

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated

Integration of Biological Sources: Exploring the Case of Protein Homology

Data integration is a key issue in the domain of bioin- formatics, which deals with huge amounts of heteroge- neous biological data that grows and changes rapidly. This paper serves as an introduction in the field of bioinformatics and the biological concepts it deals with, and an exploration of the integration problems a bioinformatics scientist faces. We examine ProGMap, an integrated protein homology system used by bioin- formatics scientists at Wageningen University, and several use cases related to protein homology. A key issue we identify is the huge manual effort required to unify source databases into a single resource. Un- certain databases are able to contain several possi- ble worlds, and it has been proposed that they can be used to significantly reduce initial integration efforts. We propose several directions for future work where uncertain databases can be applied to bioinformatics, with the goal of furthering the cause of bioinformatics integration

From Genes to Ecosystems: Resource Availability and DNA Methylation Drive the Diversity and Abundance of Restriction Modification Systems in Prokaryotes

Together, prokaryotic hosts and their viruses numerically dominate the planet and are engaged in an eternal struggle of hosts evading viral predation and viruses overcoming defensive mechanisms employed by their hosts. Prokaryotic hosts have been found to carry several viral defense systems in recent years with Restriction Modification systems (RMs) were the first discovered in the 1950s. While we have biochemically elucidated many of these systems in the last 70 years, we still struggle to understand what drives their gain and loss in prokaryotic genomes. In this work, we take a computational approach to understand the underlying evolutionary drivers of RMs by assessing ‘big data’ signals of RMs in prokaryotic genomes and incorporating molecular data in trait-based mathematical models. Focusing on the Cyanobacteria, we found a large discrepancy in the frequency of RMs per genome in different environmental contexts, where Cyanobacteria that live in oligotrophic nutrient conditions have few to no RMs and those in nutrient-rich conditions consistently have many RMs. While our models agree with the observation that increased nutrient inputs make the selective pressure of RMs more intense, they were unable to reconcile the high numbers of RMs per genome with their potent defensive properties- a situation of apparent overkill. By incorporating viral methylation, an unavoidable effect of RMs, we were able to explain how organisms could carry over 15 RMs. With this discovery, we then tried and reassess the distribution of methyltransferases, an essential component of RMs that can also have alternate physiological rolls in the cell. We expand on conventional wisdom, that methyltransferases that are widely phylogenetically conserved are associated with global cellular regulation. However, we also find that organisms with high numbers of RMs also have a surprising amount of conservation in the methyltransferases that they carry. This data suggests caution should be used in associating phylogenic signals with functional rolls in methyltransferases as different functional rolls seem to overlap in their phylogenetic signal. Indeed, we suggest trait-based modeling may be the best tool in elucidating why organisms with a high selective pressure to maintain RMs appear to have conserved methyltransferase

Expressed sequence tags from the oomycete fish pathogen Saprolegnia parasitica reveal putative virulence factors

Peer reviewedPublisher PD

Unveiling Human Non-Random Genome Editing Mechanisms Activated in Response to Chronic Environmental Changes: I. Where Might These Mechanisms Come from and What Might They Have Led To?

none1noThis article challenges the notion of the randomness of mutations in eukaryotic cells by unveiling stress-induced human non-random genome editing mechanisms. To account for the existence of such mechanisms, I have developed molecular concepts of the cell environment and cell environmental stressors and, making use of a large quantity of published data, hypothesised the origin of some crucial biological leaps along the evolutionary path of life on Earth under the pressure of natural selection, in particular, (1) virus-cell mating as a primordial form of sexual recombination and symbiosis; (2) Lamarckian CRISPR-Cas systems; (3) eukaryotic gene development; (4) antiviral activity of retrotransposon-guided mutagenic enzymes; and finally, (5) the exaptation of antiviral mutagenic mechanisms to stress-induced genome editing mechanisms directed at "hyper-transcribed" endogenous genes. Genes transcribed at their maximum rate (hyper-transcribed), yet still unable to meet new chronic environmental demands generated by "pollution", are inadequate and generate more and more intronic retrotransposon transcripts. In this scenario, RNA-guided mutagenic enzymes (e.g., Apolipoprotein B mRNA editing catalytic polypeptide-like enzymes, APOBECs), which have been shown to bind to retrotransposon RNA-repetitive sequences, would be surgically targeted by intronic retrotransposons on opened chromatin regions of the same "hyper-transcribed" genes. RNA-guided mutagenic enzymes may therefore "Lamarkianly" generate single nucleotide polymorphisms (SNP) and gene copy number variations (CNV), as well as transposon transposition and chromosomal translocations in the restricted areas of hyper-functional and inadequate genes, leaving intact the rest of the genome. CNV and SNP of hyper-transcribed genes may allow cells to surgically explore a new fitness scenario, which increases their adaptability to stressful environmental conditions. Like the mechanisms of immunoglobulin somatic hypermutation, non-random genome editing mechanisms may generate several cell mutants, and those codifying for the most environmentally adequate proteins would have a survival advantage and would therefore be Darwinianly selected. Non-random genome editing mechanisms represent tools of evolvability leading to organismal adaptation including transgenerational non-Mendelian gene transmission or to death of environmentally inadequate genomes. They are a link between environmental changes and biological novelty and plasticity, finally providing a molecular basis to reconcile gene-centred and "ecological" views of evolution.openZamai, LorisZamai, Lori

Synthetic biology advanced natural product discovery

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a limited number of natural products have been discovered, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels under conventional laboratory conditions. With the rapid development of synthetic biology, advanced genome mining and engineering strategies have been reported and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions