Current Genomics - Volume 14, Issue 6, 2013

The certain fossil record of animals begins around 540 million years ago, close to the base of the Cambrian Period. A series of extraordinary discoveries starting over 100 years ago with Walcott’s discovery of the Burgess Shale has accelerated in the last thirty years or so with the description of exceptionally-preserved Cambrian fossils from around the world. Such deposits of “Burgess Shale Type” have been recently complemented by other types of exceptional preservation. Together with a remarkable growth in knowledge about the environments that these early animals lived in, these discoveries have long exerted a fascination and strong influence on views on the origins of animals, and indeed, the nature of evolution itself. Attention is now shifting to the period of time just before animals become common, at the base of the Cambrian and in the preceding Ediacaran Period. Remarkable though the Burgess Shale deposits have been, a substantial gap still exists in our knowledge of the earliest animals. Nevertheless, the fossils from this most remarkable period of evolutionary history continue to exert a strong influence on many aspects of animal evolution, not least recent theories about developmental evolution.

This article was to have been written by Kees Weijer, an outstanding pioneer in Dictyostelium research. It was (and is) to celebrate J.T. Bonner’s and Weijer’s contributions to the field and those of the other great pioneers. Unfortunately, Weijer was unable to write his article, due to ill health and since I have some knowledge of this field, I took it over. The article summarises some main results and ideas in Dictyostelium research and their relevance for development of more advanced organisms.

The concept of homeoprotein transduction as a novel signaling pathway has dramatically evolved since it was first proposed in 1991. It is now well established in several biological systems from plants to mammals. In this review, the different steps that have led to this unexpected observation are recalled and the developmental and physiological models that have allowed us (and a few others) to consolidate the original hypothesis are described. Because homeoprotein signaling is active in plants and animals it is proposed that it has predated the separation between animals and plants and is thus very ancient. This may explain why the basic phenomenon of homeoprotein transduction is so minimalist, requiring no specific receptors or transduction pathways beside those offered by mitochondria, organelles present in all eukaryotic cells. Indeed complexity has been added in the course of evolution and the conservation of homeoprotein transduction is discussed in the context of its synergy with bona fide signaling mechanism that may have added robustness to this primitive cell communication device. The same synergy possibly explains why homeoprotein signaling is important both in embryonic development and in adult functions fulfilled by signaling entities (e.g. growth factors) themselves active throughout development and in the adult. The cell biological mechanism of homeoprotein transfer is also discussed. Although it is clear that many questions are still in want of precise answers, it appears that the sequences responsible both for secretion and internalization are in the DNA-binding domain and very highly conserved among most homeoproteins. On this basis, it is proposed that this signaling pathway is likely to imply as many as 200 proteins that participate in a myriad of developmental and physiological pathways.

The important role of non coding RNAs (ncRNAs) in the cell has made their identification a critical issue in the biological research. However, traditional approaches such as PT-PCR and Northern Blot are costly. With recent progress in bioinformatics and computational prediction technology, the discovery of ncRNAs has become realistically possible. This paper aims to introduce major computational approaches in the identification of ncRNAs, including homologous search, de novo prediction and mining in deep sequencing data. Furthermore, related software tools have been compared and reviewed along with a discussion on future improvements.

In bacteria, transcriptional regulation is a key step in cellular gene expression. All bacteria contain a core RNA polymerase that is catalytically competent but requires an additional σ factor for specific promoter recognition and correct transcriptional initiation. The RNAP core is not able to selectively bind to a given σ factor. In contrast, different σ factors have different affinities for the RNAP core. As a consequence, the concentration of alternate σ factors requires strict regulation in order to properly control the delicate interplay among them, which favors the competence for the RNAP core. This control is archived by different σ/anti-σ controlling mechanisms that shape complex regulatory networks and cascades, and enable the response to sudden environmental cues, whose global understanding is a current challenge for systems biology. Although there have been a number of excellent studies on each of these σ/anti-σ post-transcriptional regulatory systems, no comprehensive comparison of these mechanisms in a single model organism has been conducted. Here, we survey all these systems in E. coli dissecting and analyzing their inner workings and highlightin their differences. Then, following an integral approach, we identify their commonalities and outline some of the principles exploited by the cell to effectively and globally reprogram the transcriptional machinery. These principles provide guidelines for developing biological synthetic circuits enabling an efficient and robust response to sudden stimuli.

Coronary artery disease (CAD) is one of the leading causes of death in the developed countries. Myocardial infarction (MI) is an acute episode of CAD that results in myocardial injury and subsequent heart failure (HF). In the acute phase of MI several risk factors for future cardiovascular events have been found. The molecular mechanisms of these disorders are still unknown, but altered gene expression may play an important role in the development and progression of cardiovascular diseases. High-throughput techniques should greatly facilitate the elucidation of the mechanisms and provide novel insights into the pathophysiology of cardiovascular diseases. In this review we focus on the perspectives of gene-expression profiling conducted on cardiac tissues and blood for the determination of novel diagnostic and prognostic markers and therapeutic targets.

Protein interactions play an important role in the discovery of protein functions and pathways in biological processes. This is especially true in case of the diseases caused by the loss of specific protein-protein interactions in the organism. The accuracy of experimental results in finding protein-protein interactions, however, is rather dubious and high throughput experimental results have shown both high false positive beside false negative information for protein interaction. Computational methods have attracted tremendous attention among biologists because of the ability to predict protein-protein interactions and validate the obtained experimental results. In this study, we have reviewed several computational methods for protein-protein interaction prediction as well as describing major databases, which store both predicted and detected protein-protein interactions, and the tools used for analyzing protein interaction networks and improving protein-protein interaction reliability.