Degeneracy: a link between evolvability, robustness and complexity in biological systems

A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability

Skeletal muscle munc18c and syntaxin 4 in human obesity

<p>Abstract</p> <p>Background</p> <p>Animal and cell culture data suggest a critical role for Munc18c and Syntaxin 4 proteins in insulin mediated glucose transport in skeletal muscle, but no studies have been published in humans.</p> <p>Methods</p> <p>We investigated the effect of a 12 vs. 48 hr fast on insulin action and skeletal muscle Munc18c and Syntaxin 4 protein in lean and obese subjects. Healthy lean (n = 14; age = 28.0 +/- 1.4 yr; BMI = 22.8 +/- 0.42 kg/m²) and obese subjects (n = 11; age = 34.6 +/- 2.3 yr; BMI = 36.1 +/- 1.5 kg/m²) were studied twice following a 12 and 48 hr fast. Skeletal muscle biopsies were obtained before a 3 hr 40 mU/m²/min hyperinsulinemic-euglycemic clamp with [6,6-²H₂]glucose infusion.</p> <p>Results</p> <p>Glucose rate of disappearance (Rd) during the clamp was lower in obese vs. lean subjects after the 12 hr fast (obese: 6.25 +/- 0.67 vs. lean: 9.42 +/- 1.1 mg/kgFFM/min, p = 0.007), and decreased significantly in both groups after the 48 hr fast (obese 3.49 +/- 0.31 vs. lean: 3.91 +/- 0.42 mg/kgFFM/min, p = 0.002). Munc18c content was not significantly different between lean and obese subjects after the 12 hour fast, and decreased after the 48 hr fast in both groups (p = 0.013). Syntaxin 4 content was not altered by obesity or fasting duration. There was a strong positive relationship between plasma glucose concentration and Munc18c content in lean and obese subjects during both 12 and 48 hr fasts (R²= 0.447, p = 0.0015). Significant negative relationships were also found between Munc18c and FFA (p = 0.041), beta-hydroxybutyrate (p = 0.039), and skeletal muscle AKT content (p = 0.035) in lean and obese subjects.</p> <p>Conclusion</p> <p>These data indicate Munc18c and Syntaxin 4 are present in human skeletal muscle. Munc18c content was not significantly different between lean and obese subjects, and is therefore unlikely to explain obesity-induced insulin resistance. Munc18c content decreased after prolonged fasting in lean and obese subjects concurrently with reduced insulin action. These data suggest changes in Munc18c content in skeletal muscle are associated with short-term changes in insulin action in humans.</p

An Evaluation of Putative Sympatric Speciation within Limnanthes (Limnanthaceae)

Limnanthes floccosa ssp. floccosa and L. floccosa ssp. grandiflora are two of five subspecies within Limnanthes floccosa endemic to vernal pools in southern Oregon and northern California. Three seasons of monitoring natural populations have quantified that L. floccosa ssp. grandiflora is always found growing sympatrically with L. floccosa ssp. floccosa and that their flowering times overlap considerably. Despite their subspecific rank within the same species crossing experiments have confirmed that their F1 hybrids are sterile. An analysis of twelve microsatellite markers, with unique alleles in each taxon, also shows exceedingly low levels of gene flow between populations of the two subspecies. Due to the lack of previous phylogenetic resolution among L. floccosa subspecies, we used Illumina next generation sequencing to identify single nucleotide polymorphisms from genomic DNA libraries of L. floccosa ssp. floccosa and L. floccosa ssp. grandiflora. These data were used to identify single nucleotide polymorphisms in the chloroplast, mitochondrial, and nuclear genomes. From these variable loci, a total of 2772 bp was obtained using Sanger sequencing of ten individuals representing all subspecies of L. floccosa and an outgroup. The resulting phylogenetic reconstruction was fully resolved. Our results indicate that although L. floccosa ssp. floccosa and L. floccosa ssp. grandiflora are closely related, they are not sister taxa and therefore likely did not diverge as a result of a sympatric speciation event

Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

Alzheimer's Disease-Linked Mutations in Presenilin-1 Result in a Drastic Loss of Activity in Purified γ-Secretase Complexes

BACKGROUND: Mutations linked to early onset, familial forms of Alzheimer's disease (FAD) are found most frequently in PSEN1, the gene encoding presenilin-1 (PS1). Together with nicastrin (NCT), anterior pharynx-defective protein 1 (APH1), and presenilin enhancer 2 (PEN2), the catalytic subunit PS1 constitutes the core of the γ-secretase complex and contributes to the proteolysis of the amyloid precursor protein (APP) into amyloid-beta (Aβ) peptides. Although there is a growing consensus that FAD-linked PS1 mutations affect Aβ production by enhancing the Aβ1-42/Aβ1-40 ratio, it remains unclear whether and how they affect the generation of APP intracellular domain (AICD). Moreover, controversy exists as to how PS1 mutations exert their effects in different experimental systems, by either increasing Aβ1-42 production, decreasing Aβ1-40 production, or both. Because it could be explained by the heterogeneity in the composition of γ-secretase, we purified to homogeneity complexes made of human NCT, APH1aL, PEN2, and the pathogenic PS1 mutants L166P, ΔE9, or P436Q. METHODOLOGY/PRINCIPAL FINDINGS: We took advantage of a mouse embryonic fibroblast cell line lacking PS1 and PS2 to generate different stable cell lines overexpressing human γ-secretase complexes with different FAD-linked PS1 mutations. A multi-step affinity purification procedure was used to isolate semi-purified or highly purified γ-secretase complexes. The functional characterization of these complexes revealed that all PS1 FAD-linked mutations caused a loss of γ-secretase activity phenotype, in terms of Aβ1-40, Aβ1-42 and APP intracellular domain productions in vitro. CONCLUSION/SIGNIFICANCE: Our data support the view that PS1 mutations lead to a strong γ-secretase loss-of-function phenotype and an increased Aβ1-42/Aβ1-40 ratio, two mechanisms that are potentially involved in the pathogenesis of Alzheimer's disease

The malignant phenotype in breast cancer is driven by eIF4A1-mediated changes in the translational landscape

Human mRNA DeXD/H-box helicases are ubiquitous molecular motors that are required for the majority of cellular processes that involve RNA metabolism. One of the most abundant is eIF4A, which is required during the initiation phase of protein synthesis to unwind regions of highly structured mRNA that would otherwise impede the scanning ribosome. Dysregulation of protein synthesis is associated with tumorigenesis, but little is known about the detailed relationships between RNA helicase function and the malignant phenotype in solid malignancies. Therefore, immunohistochemical analysis was performed on over 3000 breast tumors to investigate the relationship among expression of eIF4A1, the helicase-modulating proteins eIF4B, eIF4E and PDCD4, and clinical outcome. We found eIF4A1, eIF4B and eIF4E to be independent predictors of poor outcome in ER-negative disease, while in contrast, the eIF4A1 inhibitor PDCD4 was related to improved outcome in ER-positive breast cancer. Consistent with these data, modulation of eIF4A1, eIF4B and PCDC4 expression in cultured MCF7 cells all restricted breast cancer cell growth and cycling. The eIF4A1-dependent translatome of MCF7 cells was defined by polysome profiling, and was shown to be highly enriched for several classes of oncogenic genes, including G-protein constituents, cyclins and protein kinases, and for mRNAs with G/C-rich 5′UTRs with potential to form G-quadruplexes and with 3′UTRs containing microRNA target sites. Overall, our data show that dysregulation of mRNA unwinding contributes to the malignant phenotype in breast cancer via preferential translation of a class of genes involved in pro-oncogenic signaling at numerous levels. Furthermore, immunohistochemical tests are promising biomarkers for tumors sensitive to anti-helicase therapies

Targeted genome engineering via zinc finger nucleases

With the development of next-generation sequencing technology, ever-expanding databases of genetic information from various organisms are available to researchers. However, our ability to study the biological meaning of genetic information and to apply our genetic knowledge to produce genetically modified crops and animals is limited, largely due to the lack of molecular tools to manipulate genomes. Recently, targeted cleavage of the genome using engineered DNA scissors called zinc finger nucleases (ZFNs) has successfully supported the precise manipulation of genetic information in various cells, animals, and plants. In this review, we will discuss the development and applications of ZFN technology for genome engineering and highlight recent reports on its use in plants

The Role of Presenilin and its Interacting Proteins in the Biogenesis of Alzheimer’s Beta Amyloid

The biogenesis and accumulation of the beta amyloid protein (Aβ) is a key event in the cascade of oxidative and inflammatory processes that characterises Alzheimer’s disease. The presenilins and its interacting proteins play a pivotal role in the generation of Aβ from the amyloid precursor protein (APP). In particular, three proteins (nicastrin, aph-1 and pen-2) interact with presenilins to form a large multi-subunit enzymatic complex (γ-secretase) that cleaves APP to generate Aβ. Reconstitution studies in yeast and insect cells have provided strong evidence that these four proteins are the major components of the γ-secretase enzyme. Current research is directed at elucidating the roles that each of these protein play in the function of this enzyme. In addition, a number of presenilin interacting proteins that are not components of γ-secretase play important roles in modulating Aβ production. This review will discuss the components of the γ-secretase complex and the role of presenilin interacting proteins on γ-secretase activity

The structure and function of Alzheimer's gamma secretase enzyme complex

The production and accumulation of the beta amyloid protein (Aβ) is a key event in the cascade of oxidative and inflammatory processes that characterizes Alzheimer’s disease (AD). A multi-subunit enzyme complex, referred to as gamma (γ) secretase, plays a pivotal role in the generation of Aβ from its parent molecule, the amyloid precursor protein (APP). Four core components (presenilin, nicastrin, aph-1, and pen-2) interact in a high-molecular-weight complex to perform intramembrane proteolysis on a number of membrane-bound proteins, including APP and Notch. Inhibitors and modulators of this enzyme have been assessed for their therapeutic benefit in AD. However, although these agents reduce Aβ levels, the majority have been shown to have severe side effects in pre-clinical animal studies, most likely due to the enzymes role in processing other proteins involved in normal cellular function. Current research is directed at understanding this enzyme and, in particular, at elucidating the roles that each of the core proteins plays in its function. In addition, a number of interacting proteins that are not components of γ-secretase also appear to play important roles in modulating enzyme activity. This review will discuss the structural and functional complexity of the γ-secretase enzyme and the effects of inhibiting its activity

SalmoNet, an integrated network of ten Salmonella enterica strains reveals common and distinct pathways to host adaptation

Salmonella enterica is a prominent bacterial pathogen with implications on human and animal health. Salmonella serovars could be classified as gastro-intestinal or extra-intestinal. Genome-wide comparisons revealed that extra-intestinal strains are closer relatives of gastro-intestinal strains than to each other indicating a parallel evolution of this trait. Given the complexity of the differences, a systems-level comparison could reveal key mechanisms enabling extra-intestinal serovars to cause systemic infections. Accordingly, in this work, we introduce a unique resource, SalmoNet, which combines manual curation, high-throughput data and computational predictions to provide an integrated network for Salmonella at the metabolic, transcriptional regulatory and protein-protein interaction levels. SalmoNet provides the networks separately for five gastro-intestinal and five extra-intestinal strains. As a multi-layered, multi-strain database containing experimental data, SalmoNet is the first dedicated network resource for Salmonella. It comprehensively contains interactions between proteins encoded in Salmonella pathogenicity islands, as well as regulatory mechanisms of metabolic processes with the option to zoom-in and analyze the interactions at specific loci in more detail. Application of SalmoNet is not limited to strain comparisons as it also provides a Salmonella resource for biochemical network modeling, host-pathogen interaction studies, drug discovery, experimental validation of novel interactions, uncovering new pathological mechanisms from emergent properties and epidemiological studies. SalmoNet is available at http://salmonet.org