A simple principle concerning the robustness of protein complex activity to changes in gene expression

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains' growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

Characterizing morphological alterations in blood related disorders through Atomic Force Microscopy

Atomic Force Microscopy (AFM) is a very flexible method that can create topographical images from a range of materials and image surfaces. Significantly, AFM has emerged as an invaluable tool for dissecting the morphology and biochemical aspects of body cells and tissues. The high-resolution imaging capabilities of AFM enable researchers to discern alterations in cell morphology and understand the underlying mechanisms of diseases. It contributes to understanding disease etiology and progression. In the context of this review, our focus will be directed towards elucidating the pivotal role of AFM in analysis of blood related disorders. Through detailed comparisons with normal cells, we delve into the alterations in size, shape, and surface characteristics induced by conditions such as cancer, diabetes, anaemia, and infections caused by pathogens. In essence, various work described in this article highlights to bridge the gap between traditional microscopy and in-depth analysis of blood-related pathologies, which in turn offers valuable perspectives for both research and clinical applications in the field.

Study of kaempferol in the treatment of COVID-19 combined with Chikungunya co-infection by network pharmacology and molecular docking technology

Chikungunya (CHIK) patients may be vulnerable to coronavirus disease (COVID-19). However, presently there are no anti-COVID-19/CHIK therapeutic alternatives available. The purpose of this research was to determine the pharmacological mechanism through which kaempferol functions in the treatment of COVID-19-associated CHIK co-infection. We have used a series of network pharmacology and computational analysis-based techniques to decipher and define the binding capacity, biological functions, pharmacological targets, and treatment processes in COVID-19-mediated CHIK co-infection. We identified key therapeutic targets for COVID-19/CHIK, including TP53, MAPK1, MAPK3, MAPK8, TNF, IL6 and NFKB1. Gene ontology, molecular and upstream pathway analysis of kaempferol against COVID-19 and CHIK showed that DEGs were confined mainly to the cytokine-mediated signalling pathway, MAP kinase activity, negative regulation of the apoptotic process, lipid and atherosclerosis, TNF signalling pathway, hepatitis B, toll-like receptor signaling, IL-17 and IL-18 signaling pathways. The study of the gene regulatory network revealed several significant TFs including KLF16, GATA2, YY1 and FOXC1 and miRNAs such as let-7b-5p, mir-16-5p, mir-34a-5p, and mir-155-5p that target differential-expressed genes (DEG). According to the molecular coupling results, kaempferol exhibited a high affinity for 5 receptor proteins (TP53, MAPK1, MAPK3, MAPK8, and TNF) compared to control inhibitors. In combination, our results identified significant targets and pharmacological mechanisms of kaempferol in the treatment of COVID-19/CHIK and recommended that core targets be used as potential biomarkers against COVID-19/CHIK viruses. Before conducting clinical studies for the intervention of COVID-19 and CHIK, kaempferol might be evaluated in wet lab tests at the molecular level.

Systematizing Microbial Bioplastic Production for Developing Sustainable Bioeconomy: Metabolic Nexus Modeling, Economic and Environmental Technologies Assessment

The excessive usage of non-renewable resources to produce plastic commodities has incongruously influenced the environment's health. Especially in the times of COVID-19, the need for plastic-based health products has increased predominantly. Given the rise in global warming and greenhouse gas emissions, the lifecycle of plastic has been established to contribute to it significantly. Bioplastics such as polyhydroxy alkanoates, polylactic acid, etc. derived from renewable energy origin have been a magnificent alternative to conventional plastics and reconnoitered exclusively for combating the environmental footprint of petrochemical plastic. However, the economically reasonable and environmentally friendly procedure of microbial bioplastic production has been a hard nut to crack due to less scouted and inefficient process optimization and downstream processing methodologies. Thereby, meticulous employment of computational tools such as genome-scale metabolic modeling and flux balance analysis has been practiced in recent times to understand the effect of genomic and environmental perturbations on the phenotype of the microorganism. In-silico results not only aid us in determining the biorefinery abilities of the model microorganism but also curb our reliance on equipment, raw materials, and capital investment for optimizing the best conditions. Additionally, to accomplish sustainable large-scale production of microbial bioplastic in a circular bioeconomy, extraction, and refinement of bioplastic needs to be investigated extensively by practicing techno-economic analysis and life cycle assessment. This review put forth state-of-the-art know-how on the proficiency of these computational techniques in laying the foundation of an efficient bioplastic manufacturing blueprint, chiefly focusing on microbial polyhydroxy alkanoates (PHA) production and its efficacy in outplacing fossil based plastic products.

The emergence of polyglot entrainment responses to periodic inputs in vicinities of Hopf bifurcations in slow-fast systems

Several distinct entrainment patterns can occur in the FitzHugh-Nagumo (FHN) model under external periodic forcing. Investigating the FHN model under different types of periodic forcing reveals the existence of multiple disconnected 1:1 entrainment segments for constant, low enough values of the input amplitude when the unforced system is in the vicinity of a Hopf bifurcation. This entrainment structure is termed polyglot to distinguish it from the single 1:1 entrainment region (monoglot) structure typically observed in Arnold tongue diagrams. The emergence of polyglot entrainment is then explained using phase-plane analysis and other dynamical system tools. Entrainment results are investigated for other slow-fast systems of neuronal, circadian, and glycolytic oscillations. Exploring these models, we found that polyglot entrainment structure (multiple 1:1 regions) is observed when the unforced system is in the vicinity of a Hopf bifurcation and the Hopf point is located near a knee of a cubic-like nullcline.

Retention of duplicated genes in evolution

Gene duplication is a prevalent phenomenon across the tree of life. The processes that lead to the retention of duplicated genes are not well understood. Functional genomics approaches in model organisms, such as yeast, provide useful tools to test the mechanisms underlying retention with functional redundancy and divergence of duplicated genes, including fates associated with neofunctionalization, subfunctionalization, back-up compensation, and dosage amplification. Duplicated genes may also be retained as a consequence of structural and functional entanglement. Advances in human gene editing have enabled the interrogation of duplicated genes in the human genome, providing new tools to evaluate the relative contributions of each of these factors to duplicate gene retention and the evolution of genome structure.

Estimation of metabolic fluxes distribution in Saccharomyces cerevisiae during the production of volatile compounds of Tequila

A stoichiometric model for Saccharomyces cerevisiae is reconstructed to analyze the continuous fermentation process of agave juice in Tequila production. The metabolic model contains 94 metabolites and 117 biochemical reactions. From the above set of reactions, 93 of them are linked to internal biochemical reactions and 24 are related to transport fluxes between the medium and the cell. The central metabolism of S. cerevisiae includes the synthesis for 20 amino-acids, carbohydrates, lipids, DNA and RNA. Using flux balance analysis (FBA), different physiological states of S. cerevisiae are shown during the fermentative process; these states are compared with experimental data under different dilution rates (0.04-0.12 h$ ^{-1} $). Moreover, the model performs anabolic and catabolic biochemical reactions for the production of higher alcohols. The importance of the Saccharomyces cerevisiae genomic model in the area of alcoholic beverage fermentation is due to the fact that it allows to estimate the metabolic fluxes during the beverage fermentation process and a physiology state of the microorganism.

Expression attenuation as a mechanism of robustness against gene duplication

Gene duplication is ubiquitous and a major driver of phenotypic diversity across the tree of life, but its immediate consequences are not fully understood. Deleterious effects would decrease the probability of retention of duplicates and prevent their contribution to long-term evolution. One possible detrimental effect of duplication is the perturbation of the stoichiometry of protein complexes. Here, we measured the fitness effects of the duplication of 899 essential genes in the budding yeast using high-resolution competition assays. At least 10% of genes caused a fitness disadvantage when duplicated. Intriguingly, the duplication of most protein complex subunits had small to nondetectable effects on fitness, with few exceptions. We selected four complexes with subunits that had an impact on fitness when duplicated and measured the impact of individual gene duplications on their protein-protein interactions. We found that very few duplications affect both fitness and interactions. Furthermore, large complexes such as the 26S proteasome are protected from gene duplication by attenuation of protein abundance. Regulatory mechanisms that maintain the stoichiometric balance of protein complexes may protect from the immediate effects of gene duplication. Our results show that a better understanding of protein regulation and assembly in complexes is required for the refinement of current models of gene duplication.

Assessment of colon cancer molecular mechanism: a system biology approach

AIM

The current study aimed to assess and compare colon cancer dysregulated genes from the GEO and STRING databases.

BACKGROUND

Colorectal cancer is known as the third most common kind of cancer and the second most important reason for global cancer-related mortality rates. There have been many studies on the molecular mechanism of colon cancer.

METHODS

From the STRING database, 100 differentially expressed proteins related to colon cancers were retrieved and analyzed by network analysis. The central nodes of the network were assessed by gene ontology. The findings were compared with a GSE from GEO.

RESULTS

Based on data from the STRING database, TP53, EGFR, HRAS, MYC, AKT1, GAPDH, KRAS, ERBB2, PTEN, and VEGFA were identified as central genes. The central nodes were not included in the significant DEGs of the analyzed GSE.

CONCLUSION

A combination of different database sources in system biology investigations provides useful information about the studied diseases.

The genetic regulation of size variation in the transcriptome of the cerebrum in the chicken and its role in domestication and brain size evolution

Background

Large difference in cerebrum size exist between avian species and populations of the same species and is believed to reflect differences in processing power, i.e. in the speed and efficiency of processing information in this brain region. During domestication chickens developed a larger cerebrum compared to their wild progenitor, the Red jungle fowl. The underlying mechanisms that control cerebrum size and the extent to which genetic regulation is similar across brain regions is not well understood. In this study, we combine measurement of cerebrum size with genome-wide genetical genomics analysis to identify the genetic architecture of the cerebrum, as well as compare the regulation of gene expression in this brain region with gene expression in other regions of the brain (the hypothalamus) and somatic tissue (liver).

Results

We identify one candidate gene that putatively regulates cerebrum size (MTF2) as well as a large number of eQTL that regulate the transcriptome in cerebrum tissue, with the majority of these eQTL being trans-acting. The overall regulation of gene expression variation in the cerebrum was markedly different to the hypothalamus, with relatively few eQTL in common. In comparison, the cerebrum tissue shared more eQTL with a distant tissue (liver) than with a neighboring tissue (hypothalamus).

Conclusion

The candidate gene for cerebrum size (MTF2) has previously been linked to brain development making it a good candidate for further investigation as a regulator of inter-population variation in cerebrum size. The lack of shared eQTL between the two brain regions implies that genetic regulation of gene expression appears to be relatively independent between the two brain regions and suggest that coevolution between these two brain regions might be more functionally driven than developmental. These findings have relevance for current brain size evolution theories.

Quantitative analysis of proteins which are members of the same protein complex but cause locus heterogeneity in disease

It is still largely unknown how mutations in different genes cause similar diseases – a condition known as locus heterogeneity. A likely explanation is that the different proteins encoded by the locus heterogeneity genes participate in the same biological function and, specifically, that they belong to the same protein complex. Here we report that, in up to 30% of the instances of locus heterogeneity, the disease-causing proteins are indeed members of the same protein complex. Moreover, we observed that, in many instances, the diseases and protein complexes only partially intersect. Among the possible explanations, we surmised that some genes that encode proteins in the complex have not yet been reported as causing disease and are therefore candidate disease genes. Mutations of known human disease genes and murine orthologs of candidate disease genes that encode proteins in the same protein complex do in fact often cause similar phenotypes in humans and mice. Furthermore, we found that the disease-complex intersection is not only incomplete but also non-univocal, with many examples of one disease intersecting more than one protein complex or one protein complex intersecting more than one disease. These limits notwithstanding, this study shows that action on proteins in the same complex is a widespread pathogenic mechanism underlying numerous instances of locus heterogeneity.

Link clustering explains non-central and contextually essential genes in protein interaction networks

Recent studies have shown that many essential genes (EGs) change their essentiality across various contexts. Finding contextual EGs in pathogenic conditions may facilitate the identification of therapeutic targets. We propose link clustering as an indicator of contextual EGs that are non-central in protein-protein interaction (PPI) networks. In various human and yeast PPI networks, we found that 29–47% of EGs were better characterized by link clustering than by centrality. Importantly, non-central EGs were prone to change their essentiality across different human cell lines and between species. Compared with central EGs and non-EGs, non-central EGs had intermediate levels of expression and evolutionary conservation. In addition, non-central EGs exhibited a significant impact on communities at lower hierarchical levels, suggesting that link clustering is associated with contextual essentiality, as it depicts locally important nodes in network structures.

The role of protein complexes in human genetic disease

Many human genetic disorders are caused by mutations in protein-coding regions of DNA. Taking protein structure into account has therefore provided key insight into the molecular mechanisms underlying human genetic disease. Although most studies have focused on the intramolecular effects of mutations, the critical role of the assembly of proteins into complexes is being increasingly recognized. Here, we review multiple ways in which consideration of protein complexes can help us to understand and explain the effects of pathogenic mutations. First, we discuss disorders caused by mutations that perturb intersubunit interactions in homomeric and heteromeric complexes. Second, we address how protein complex assembly can facilitate a dominant-negative mechanism, whereby mutated subunits can disrupt the activity of wild-type protein. Third, we show how mutations that change protein expression levels can lead to damaging stoichiometric imbalances. Finally, we review how mutations affecting different subunits of the same heteromeric complex often cause similar diseases, whereas mutations in different interfaces of the same subunit can cause distinct phenotypes.

Towards Digital Manufacturing of Smart Multimaterial Fibers

Fibers are ubiquitous and usually passive. Optoelectronics realized in a fiber could revolutionize multiple application areas, including biosynthetic and wearable electronics, environmental sensing, and energy harvesting. However, the realization of high-performance electronics in a fiber remains a demanding challenge due to the elusiveness of a material processing strategy that would allow the wrapping of devices made in crystalline semiconductors, such as silicon, into a fiber in an ordered, addressable, and scalable manner. Current fiber-sensor fabrication approaches either are non-scalable or limit the choice of semiconductors to the amorphous ones, such as chalcogenide glasses, inferior to silicon in their electronic performance, resulting in limited bandwidth and sensitivity of such sensors when compared to a standard silicon photodiode. Our group substantiates a universal in-fiber manufacturing of logic circuits and sensory systems analogous to very large-scale integration (VLSI), which enabled the emergence of the modern microprocessor. We develop a versatile hybrid-fabrication methodology that assembles in-fiber material architectures typical to integrated microelectronic devices and systems in silica, silicon, and high-temperature metals. This methodology, dubbed "VLSI for Fibers," or "VLSI-Fi," combines 3D printing of preforms, a thermal draw of fibers, and post-draw assembly of fiber-embedded integrated devices by means of material-selective spatially coherent capillary breakup of the fiber cores. We believe that this method will deliver a new class of durable, low cost, pervasive fiber devices, and sensors, enabling integration of fabrics met with human-made objects, such as furniture and apparel, into the Internet of Things (IoT). Furthermore, it will boost innovation in 3D printing, extending the digital manufacturing approach into the nanoelectronics realm.

The impact of Megf10/Drpr gain-of-function on muscle development in Drosophila

Recessive mutations in multiple epidermal growth factor-like domains 10 (MEGF10) underlie a rare congenital muscle disease known as MEGF10 myopathy. MEGF10 and its Drosophila homolog Draper (Drpr) are transmembrane receptors expressed in muscle and glia. Drpr deficiency is known to result in muscle abnormalities in flies. In the current study, flies that ubiquitously overexpress Drpr, or mouse Megf10, display developmental arrest. The phenotype is reproduced with overexpression in muscle, but not in other tissues, and with overexpression during intermediate stages of myogenesis, but not in myoblasts. We find that tubular muscle subtypes are particularly sensitive to Megf10/Drpr overexpression. Complementary genetic analyses show that Megf10/Drpr and Notch may interact to regulate myogenesis. Our findings provide a basis for investigating MEGF10 in muscle development using Drosophila.

The OsPS1-F gene regulates growth and development in rice by modulating photosynthetic electron transport rate

Ds insertion in rice OsPS1-F gene results in semi-dwarf plants with reduced tiller number and grain yield, while genetic complementation with OsPS1-F rescued the mutant phenotype. Photosynthetic electron transport is regulated in the chloroplast thylakoid membrane by multi-protein complexes. Studies about photosynthetic machinery and its subunits in crop plants are necessary, because they could be crucial for yield enhancement in the long term. Here, we report the characterization of OsPS1-F (encoding Oryza sativa PHOTOSYSTEM 1-F subunit) using a single copy Ds insertion rice mutant line. The homozygous mutant (osps1-f) showed striking difference in growth and development compared to the wild type (WT), including, reduction in plant height, tiller number, grain yield as well as pale yellow leaf coloration. Chlorophyll concentration and electron transport rate were significantly reduced in the mutant compared to the WT. OsPS1-F gene was highly expressed in rice leaves compared to other tissues at different developmental stages tested. Upon complementation of the mutant with proUBI::OsPS1-F, the observed mutant phenotypes were rescued. Our results illustrate that OsPS1-F plays an important role in regulating proper growth and development of rice plants.

Endocytic recycling protein EHD1 regulates primary cilia morphogenesis and SHH signaling during neural tube development

Members of the four-member C-terminal EPS15-Homology Domain-containing (EHD) protein family play crucial roles in endocytic recycling of cell surface receptors from endosomes to the plasma membrane. In this study, we show that Ehd1 gene knockout in mice on a predominantly B6 background is embryonic lethal. Ehd1-null embryos die at mid-gestation with a failure to complete key developmental processes including neural tube closure, axial turning and patterning of the neural tube. We found that Ehd1-null embryos display short and stubby cilia on the developing neuroepithelium at embryonic day 9.5 (E9.5). Loss of EHD1 also deregulates the ciliary SHH signaling with Ehd1-null embryos displaying features indicative of increased SHH signaling, including a significant downregulation in the formation of the GLI3 repressor and increase in the ventral neuronal markers specified by SHH. Using Ehd1-null MEFS we found that EHD1 protein co-localizes with the SHH receptor Smoothened in the primary cilia upon ligand stimulation. Under the same conditions, EHD1 was shown to co-traffic with Smoothened into the developing primary cilia and we identify EHD1 as a direct binding partner of Smoothened. Overall, our studies identify the endocytic recycling regulator EHD1 as a novel regulator of the primary cilium-associated trafficking of Smoothened and Hedgehog signaling.

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker's or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/ for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow-tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow-tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems.

Exploring the evolutionary rate differences between human disease and non-disease genes

Comparisons of evolutionary features between human disease and non-disease genes have a wide implication to understand the genetic basis of human disease genes. However, it has not yet been resolved whether disease genes evolve at slower or faster rate than the non-disease genes. To resolve this controversy, here we integrated human disease genes from several databases and compared their protein evolutionary rates with non-disease genes in both housekeeping and tissue-specific group. We noticed that in tissue specific group, disease genes evolve significantly at a slower rate than non-disease genes. However, we found no significant difference in evolutionary rates between disease and non-disease genes in housekeeping group. Tissue specific disease genes have a higher protein complex number, elevated gene expression level and are also associated with conserve biological processes. Finally, our regression analysis suggested that protein complex number followed by protein multifunctionality independently modulates the evolutionary rate of human disease genes.

Concerted copy number variation balances ribosomal DNA dosage in human and mouse genomes

Tandemly repeated ribosomal DNA (rDNA) arrays are among the most evolutionary dynamic loci of eukaryotic genomes. The loci code for essential cellular components, yet exhibit extensive copy number (CN) variation within and between species. CN might be partly determined by the requirement of dosage balance between the 5S and 45S rDNA arrays. The arrays are nonhomologous, physically unlinked in mammals, and encode functionally interdependent RNA components of the ribosome. Here we show that the 5S and 45S rDNA arrays exhibit concerted CN variation (cCNV). Despite 5S and 45S rDNA elements residing on different chromosomes and lacking sequence similarity, cCNV between these loci is strong, evolutionarily conserved in humans and mice, and manifested across individual genotypes in natural populations and pedigrees. Finally, we observe that bisphenol A induces rapid and parallel modulation of 5S and 45S rDNA CN. Our observations reveal a novel mode of genome variation, indicate that natural selection contributed to the evolution and conservation of cCNV, and support the hypothesis that 5S CN is partly determined by the requirement of dosage balance with the 45S rDNA array. We suggest that human disease variation might be traced to disrupted rDNA dosage balance in the genome.

All or nothing: protein complexes flip essentiality between distantly related eukaryotes

In the budding yeast Saccharomyces cerevisiae, the subunits of any given protein complex are either mostly essential or mostly nonessential, suggesting that essentiality is a property of molecular machines rather than individual components. There are exceptions to this rule, however, that is, nonessential genes in largely essential complexes and essential genes in largely nonessential complexes. Here, we provide explanations for these exceptions, showing that redundancy within complexes, as revealed by genetic interactions, can explain many of the former cases, whereas “moonlighting,” as revealed by membership of multiple complexes, can explain the latter. Surprisingly, we find that redundancy within complexes cannot usually be explained by gene duplication, suggesting alternate buffering mechanisms. In the distantly related Schizosaccharomyces pombe, we observe the same phenomenon of modular essentiality, suggesting that it may be a general feature of eukaryotes. Furthermore, we show that complexes flip essentiality in a cohesive fashion between the two species, that is, they tend to change from mostly essential to mostly nonessential, or vice versa, but not to mixed patterns. We show that these flips in essentiality can be explained by differing lifestyles of the two yeasts. Collectively, our results support a previously proposed model where proteins are essential because of their involvement in essential functional modules rather than because of specific topological features such as degree or centrality.

Evolutionary rate heterogeneity of core and attachment proteins in yeast protein complexes

In general, proteins do not work alone; they form macromolecular complexes to play fundamental roles in diverse cellular functions. On the basis of their iterative clustering procedure and frequency of occurrence in the macromolecular complexes, the protein subunits have been categorized as core and attachment. Core protein subunits are the main functional elements, whereas attachment proteins act as modifiers or activators in protein complexes. In this article, using the current data set of yeast protein complexes, we found that core proteins are evolving at a faster rate than attachment proteins in spite of their functional importance. Interestingly, our investigation revealed that attachment proteins are present in a higher number of macromolecular complexes than core proteins. We also observed that the protein complex number (defined as the number of protein complexes in which a protein subunit belongs) has a stronger influence on gene/protein essentiality than multifunctionality. Finally, our results suggest that the observed differences in the rates of protein evolution between core and attachment proteins are due to differences in protein complex number and expression level. Moreover, we conclude that proteins which are present in higher numbers of macromolecular complexes enhance their overall expression level by increasing their transcription rate as well as translation rate, and thus the protein complex number imposes a strong selection pressure on the evolution of yeast proteome.

Evolutionary diversification of the multimeric states of proteins

One of the most striking features of proteins is their common assembly into multimeric structures, usually homomers with even numbers of subunits all derived from the same genetic locus. However, although substantial structural variation for orthologous proteins exists within and among major phylogenetic lineages, in striking contrast to patterns of gene structure and genome organization, there appears to be no correlation between the level of protein structural complexity and organismal complexity. In addition, there is no evidence that protein architectural differences are driven by lineage-specific differences in selective pressures. Here, it is suggested that variation in the multimeric states of proteins can readily arise from stochastic transitions resulting from the joint processes of mutation and random genetic drift, even in the face of constant directional selection for one particular protein architecture across all lineages. Under the proposed hypothesis, on a long evolutionary timescale, the numbers of transitions from monomers to dimers should approximate the numbers in the opposite direction and similarly for transitions between higher-order structures.

A systematic approach for the genetic dissection of protein complexes in living cells

Cells contain many important protein complexes involved in performing and regulating structural, metabolic, and signaling functions. One major challenge in cell biology is to elucidate the organization and mechanisms of robustness of these complexes in vivo. We developed a systematic approach to study structural dependencies within complexes in living cells by deleting subunits and measuring pairwise interactions among other components. We used our methodology to perturb two conserved eukaryotic complexes: the retromer and the nuclear pore complex. Our results identify subunits that are critical for the assembly of these complexes, reveal their structural architecture, and uncover mechanisms by which protein interactions are modulated. Our results also show that paralogous proteins play a key role in the robustness of protein complexes and shape their assembly landscape. Our approach paves the way for studying the response of protein interactomes to mutations and enhances our understanding of genotype-phenotype maps.

The evolution of multimeric protein assemblages

Although the mechanisms by which complex cellular features evolve constitute one of the great unsolved problems of evolutionary biology, it is clear that the emergence of new protein-protein interactions, often accompanied by the diversification of duplicate genes, is involved. Using information on the levels of protein multimerization in major phylogenetic groups as a guide to the patterns that must be explained and relying on results from population-genetic theory to define the relative plausibility of alternative evolutionary pathways, a framework for understanding the evolution of dimers is developed. The resultant theory demonstrates that the likelihoods of alternative pathways for the emergence of protein complexes depend strongly on the effective population size. Nonetheless, it is equally clear that further advancements in this area will require comparative studies on the fitness consequences of alternative monomeric and dimeric proteins.

The repatterning of eukaryotic genomes by random genetic drift

Recent observations on rates of mutation, recombination, and random genetic drift highlight the dramatic ways in which fundamental evolutionary processes vary across the divide between unicellular microbes and multicellular eukaryotes. Moreover, population-genetic theory suggests that the range of variation in these parameters is sufficient to explain the evolutionary diversification of many aspects of genome size and gene structure found among phylogenetic lineages. Most notably, large eukaryotic organisms that experience elevated magnitudes of random genetic drift are susceptible to the passive accumulation of mutationally hazardous DNA that would otherwise be eliminated by efficient selection. Substantial evidence also suggests that variation in the population-genetic environment influences patterns of protein evolution, with the emergence of certain kinds of amino-acid substitutions and protein-protein complexes only being possible in populations with relatively small effective sizes. These observations imply that the ultimate origins of many of the major genomic and proteomic disparities between prokaryotes and eukaryotes and among eukaryotic lineages have been molded as much by intrinsic variation in the genetic and cellular features of species as by external ecological forces.

Integrated genome-scale prediction of detrimental mutations in transcription networks

A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or “edge”) rather than a gene (or “node”) in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.

The genomes of individuals differ in sequence at thousands of base pairs. Some of these polymorphisms affect the sequence of proteins, but many are likely to alter how genes are regulated. When are changes in gene regulation detrimental to an organism? We have used an integrative analysis of transcription factor binding site conservation in budding yeast to address the extent to which different features predict when potential changes in gene regulation are detrimental. We found that, despite the diversity of transcription factors and regulatory regions in a genome, a few simple properties can be used to predict and understand when changes in regulation are most harmful.

Alterations of EHD1/EHD4 protein levels interfere with L1/NgCAM endocytosis in neurons and disrupt axonal targeting

Axon growth is regulated by many proteins, including adhesion molecules, which need to be trafficked correctly to axons. The adhesion molecule L1/neuron-glia cell adhesion molecule (NgCAM) travels to axons via an endocytosis-dependent pathway (transcytosis), traversing somatodendritic endosomes. The Eps15 homology domain (EHD) family proteins (EHD1-EHD4) play important roles in endosomal recycling and possibly in endocytosis. We investigated whether EHD1 regulates L1/NgCAM trafficking in neurons. Both short hairpin-mediated downregulation and overexpression of EHD1 led to dendritic mistargeting of NgCAM. Downregulation of EHD1 showed increased endosomal accumulation of NgCAM, whereas, surprisingly, overexpression of EHD1 led to impairment of L1/NgCAM internalization in neurons but not in fibroblasts. Transferrin internalization, however, was unaffected. At longer overexpression times of EHD1, NgCAM endocytosis returned to normal, suggesting rapid upregulation of compensatory endocytic pathways. EHD1 is capable of hetero-oligomerization, and an endogenous complex of EHD1 and EHD4 was identified previously. We therefore tested whether short-term overexpression of other EHD family members showed a similar endocytosis defect. Expression of EHD4, but not of EHD3, also caused a defect in L1/NgCAM endocytosis. Oligomerization of EHD1 was required to cause NgCAM endocytosis defects, and simultaneous expression of EHD1 and EHD4 rescued NgCAM endocytosis. Therefore, balanced levels of EHD1-EHD4 are important for NgCAM endocytosis in neurons. Our data suggest that EHD1 plays roles in both endosomal recycling and a specialized endocytosis pathway in neurons used by NgCAM. We propose that EHD1 and EHD4 act as hetero-oligomeric complexes in this pathway.

Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity

Why are genes harmful when they are overexpressed? By testing possible causes of overexpression phenotypes in yeast, we identify intrinsic protein disorder as an important determinant of dosage sensitivity. Disordered regions are prone to make promiscuous molecular interactions when their concentration is increased, and we demonstrate that this is the likely cause of pathology when genes are overexpressed. We validate our findings in two animals, Drosophila melanogaster and Caenorhabditis elegans. In mice and humans the same properties are strongly associated with dosage-sensitive oncogenes, such that mass-action-driven molecular interactions may be a frequent cause of cancer. Dosage-sensitive genes are tightly regulated at the transcriptional, RNA, and protein levels, which may serve to prevent harmful increases in protein concentration under physiological conditions. Mass-action-driven interaction promiscuity is a single theoretical framework that can be used to understand, predict, and possibly treat the effects of increased gene expression in evolution and disease.

On gene dosage balance in protein complexes: a comment on Semple JI, Vavouri T, Lehner B. A simple principle concerning the robustness of protein complex activity to changes in gene expression

A comment on Semple JI, Vavouri T, Lehner B. A simple principle concerning the robustness of protein complex activity to changes in gene expression. BMC Syst Biol. 2008;2:1

Selection to minimise noise in living systems and its implications for the evolution of gene expression

Gene expression, like many biological processes, is subject to noise. This noise has been measured on a global scale, but its general importance to the fitness of an organism is unclear. Here, I show that noise in gene expression in yeast has evolved to prevent harmful stochastic variation in the levels of genes that reduce fitness when their expression levels change. Therefore, there has probably been widespread selection to minimise noise in gene expression. Selection to minimise noise, because it results in gene expression that is stable to stochastic variation in cellular components, may also constrain the ability of gene expression to respond to non-stochastic variation. I present evidence that this has indeed been the case in yeast. I therefore conclude that gene expression noise is an important biological trait, and one that probably limits the evolvability of complex living systems.