A framework for incorporating functional interrelationships into protein function prediction algorithms

The functional annotation of proteins is one of the most important tasks in the post-genomic era. Although many computational approaches have been developed in recent years to predict protein function, most of these traditional algorithms do not take interrelationships among functional terms into account, such as different GO terms usually coannotate with some common proteins. In this study, we propose a new functional similarity measure in the form of Jaccard coefficient to quantify these interrelationships and also develop a framework for incorporating GO term similarity into protein function prediction process. The experimental results of cross-validation on S. cerevisiae and Homo sapiens data sets demonstrate that our method is able to improve the performance of protein function prediction. In addition, we find that small size terms associated with a few of proteins obtain more benefit than the large size ones when considering functional interrelationships. We also compare our similarity measure with other two widely used measures, and results indicate that when incorporated into function prediction algorithms, our proposed measure is more effective. Experiment results also illustrate that our algorithms outperform two previous competing algorithms, which also take functional interrelationships into account, in prediction accuracy. Finally, we show that our method is robust to annotations in the database which are not complete at present. These results give new insights about the importance of functional interrelationships in protein function prediction.     

A comparison of two predator-prey models with Holling's type I functional response

In this paper, we analyze a laissez-faire predator-prey model and a Leslie-type predator-prey model with type I functional responses. We study the stability of the equilibrium where the predator and prey coexist by both performing a linearized stability analysis and by constructing a Lyapunov function. For the Leslie-type model, we use a generalized Jacobian to determine how eigenvalues jump at the corner of the functional response. We show, numerically, that our two models can both possess two limit cycles that surround a stable equilibrium and that these cycles arise through global cyclic-fold bifurcations. The Leslie-type model may also exhibit super-critical and discontinuous Hopf bifurcations. We then present and analyze a new functional response, built around the arctangent, that smoothes the sharp corner in a type I functional response. For this new functional response, both models undergo Hopf, cyclic-fold, and Bautin bifurcations. We use our analyses to characterize predator-prey systems that may exhibit bistability.     

Royal Society discussion meeting: utilising the genome sequence of parasitic protozoa

Protozoan parasites cause some of the world's most important diseases. Genome sequencing information is rapidly being acquired and combined with new developments in functional genome analysis to transform our understanding of parasites, and to enable new approaches to combating the diseases they cause.     

A New Multi-label Classifier for Identifying the Functional Types of Singleplex and Multiplex Antimicrobial Peptides

Antimicrobial peptides (AMPs) play an important role in the innate immune system that evolved in most living organisms. As a kind of natural antibiotics, it is promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop a fast and effective computational method for accurately predicting the functional types of AMPs, because the biological functions of AMPs are correlated with the type it belongs to. Although many efforts have been made in this area, to the best of our knowledge, most of the existing predictors only has the ability to deal with whether a peptide is an AMP or not, or a peptide belongs to which one type. However, there are many AMPs have two or more functional types, the phenomenon should worthy of our special notice, because they may have some unique biological functions for new drug design and disease treatment. In this study, in order to reflect the characteristic of multiplex AMPs, a new multi-label classifier based on sequence information and multi-label learning with label-specific features (LIFT) algorithm was developed. It was observed that, the absolute-true with jackknife test by the new predictor on a newly stringent benchmark dataset is 0.5040, and the success rates achieved by the new predictor are 5 % higher than this by iAMP-2L in the same dataset, indicating that our method is quite promising. We hope that the predictor may become a useful high-through tool in identifying the functional types of AMPs.     

Fungal functional ecology: bringing a trait‐based approach to plant‐associated fungi

Fungi play many essential roles in ecosystems. They facilitate plant access to nutrients and water, serve as decay agents that cycle carbon and nutrients through the soil, water and atmosphere, and are major regulators of macro‐organismal populations. Although technological advances are improving the detection and identification of fungi, there still exist key gaps in our ecological knowledge of this kingdom, especially related to function . Trait‐based approaches have been instrumental in strengthening our understanding of plant functional ecology and, as such, provide excellent models for deepening our understanding of fungal functional ecology in ways that complement insights gained from traditional and ‐omics‐based techniques. In this review, we synthesize current knowledge of fungal functional ecology, taxonomy and systematics and introduce a novel database of fungal functional traits (Fun^Fun). Fun^Fun is built to interface with other databases to explore and predict how fungal functional diversity varies by taxonomy, guild, and other evolutionary or ecological grouping variables. To highlight how a quantitative trait‐based approach can provide new insights, we describe multiple targeted examples and end by suggesting next steps in the rapidly growing field of fungal functional ecology.     

3D Genomics

Molecular Biology - The development of new research methods significantly changed our views on the role that the 3D organization of the genome plays in its functional activity. It was found that...     

Innovative approaches to novel antibacterial drug discovery

Increasing antibiotic resistance in microorganisms and new emerging pathogens have become a major problem in our society. Rising to satisfy this urgent medical need is a recent confluence of powerful new drug discovery technologies: combinatorial chemistry; sequence and functional genomic analysis; and novel methods of high-throughput screening. The combination of these technologies will bring to bear untapped power in the search for new antimicrobials.     

Biocatalytic synthesis of hydroxylated natural products using aldolases and related enzymes

Synthetic building blocks bearing hydroxylated chiral centers are important targets for biocatalysis. Many C-C bond forming enzymes have recently been investigated for new applications and new strategies towards the synthesis of natural products and related oxygenated compounds. Several old catalysts have been studied to increase our functional knowledge of natural aldolase-type enzymes, and new mutated catalysts or catalytic antibodies have been tested for their synthetic utility.     

The identification of new genes: Gene trapping in transgenic mice

Ongoing efforts to clone, sequence and map genes in the mouse have far exceeded our ability to define their functional role. The generation of mutations is an important first step towards understanding the function of genes in normal mouse development and physiology. Gene trapping in embryonic stem cells provides an efficient method to identify, clone and mutate genes at random, permitting the functional analysis of new genes in mice.     

Genomes, free radicals and plant cell invasion: recent developments in plant pathogenic fungi

This review describes current advances in our understanding of fungal-plant interactions. The widespread application of whole genome sequencing to a diverse range of fungal species has allowed new insight into the evolution of fungal pathogenesis and the definition of the gene inventories associated with important plant pathogens. This has also led to functional genomic approaches to carry out large-scale gene functional analysis. There has also been significant progress in understanding appressorium-mediated plant infection by fungi and its underlying genetic basis. The nature of biotrophic proliferation of fungal pathogens in host tissue has recently revealed new potential mechanisms for cell-to-cell movement by invading pathogens.     

基因组功能预测的进化印记方法

改善基因组功能预测方案是目前功能基因组学的迫切问题,生物进化历程会在分子序列上留下相应进化印记－直系同源簇的特异模体,在这一生物学事实的基础上,提出了一个新的基因缚功能预测方法,首先利用进化分析方法构建直系同源簇,再找到各直系同源簇的功能模体,这样可以形成特异的功能模体库,未知基因的功能预测可望通过搜索该功能模体库而得以高效,准确地完成,对５个家族的检验初步证实该方案是可行的。     

Elementary Flux Modes Analysis of Functional Domain Networks Allows a Better Metabolic Pathway Interpretation

Metabolic network analysis is an important step for the functional understanding of biological systems. In these networks, enzymes are made of one or more functional domains often involved in different catalytic activities. Elementary flux mode (EFM) analysis is a method of choice for the topological studies of these enzymatic networks. In this article, we propose to use an EFM approach on networks that encompass available knowledge on structure-function. We introduce a new method that allows to represent the metabolic networks as functional domain networks and provides an application of the algorithm for computing elementary flux modes to analyse them. Any EFM that can be represented using the classical representation can be represented using our functional domain network representation but the fine-grained feature of functional domain networks allows to highlight new connections in EFMs. This methodology is applied to the tricarboxylic acid cycle (TCA cycle) of Bacillus subtilis, and compared to the classical analyses. This new method of analysis of the functional domain network reveals that a specific inhibition on the second domain of the lipoamide dehydrogenase (pdhD) component of pyruvate dehydrogenase complex leads to the loss of all fluxes. Such conclusion was not predictable in the classical approach.     

Structural aspects of AMPA receptor activation, desensitization and deactivation

Glutamate mediates most of the excitatory neurotransmission in the mammalian central nervous system by activating ionotropic glutamate receptors. Structural and functional studies of ionotropic glutamate receptors have offered detailed insight into the mechanism by which these integral membrane proteins function. In particular, advances in our understanding of the atomic structure of the agonist-binding domain have provided new opportunities to consider the conformational changes that take place in a functioning ligand-gated ion channel. Several recent studies have turned up important new ideas about the structural determinants of channel activation, deactivation and desensitization of AMPA receptors. Working hypotheses derived from this structural insight offer a rare opportunity to enrich and guide functional studies.     

Generation of evolutionary novelty by functional shift

That biological features may change their function during evolution has long been recognized. Particularly, the acquisition of new functions by molecules involved in developmental pathways is suspected to cause important morphologic novelties. However, the current terminology describing functional changes during evolution (co-option or recruitment) fails to recognize important biologic distinctions between diverse evolutionary routes involving functional shifts. The main goal of our work is to stress the importance of an apparently trivial distinction: Whether or not the element that adopts a new function (anything from a morphologic structure to a protein domain) is a single or a duplicated element. We propose that natural selection must act in a radically different way, depending on the historic succession of co-option and duplication events; that is, co-option may provide the selective pressure for a subsequent gene duplication or could be a stabilizing factor that helps maintain redundancy after gene duplication. We review the evidence available on functional changes, focusing whenever possible on developmental molecules, and we propose a conceptual framework for the study of functional shifts during evolution with a level of resolution appropriate to the power of our current methodologies. BioEssays 21:432–439, 1999. © 1999 John Wiley & Sons, Inc.     

Inference of functional properties from large-scale analysis of enzyme superfamilies

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.     

Consistent dissection of the protein interaction network by combining global and local metrics

We propose a new network decomposition method to systematically identify protein interaction modules in the protein interaction network. Our method incorporates both a global metric and a local metric for balance and consistency. We have compared the performance of our method with several earlier approaches on both simulated and real datasets using different criteria, and show that our method is more robust to network alterations and more effective at discovering functional protein modules.     

元蛋白质组学在微生物功能研究中的应用

后基因组时代,仅依靠基因组方法来研究原位微生物群落的功能已远远不够,在这种背景下元蛋白质组学研究逐渐兴起。应用元蛋白质组学技术可大规模研究原位微生物群落的蛋白质表达,分析生态系统中微生物的功能,寻找新的功能基因和代谢通路,为微生物群体的基因和功能多样性研究提供数据。同时,还可鉴定与微生物功能相关的蛋白质,这些蛋白质未来可以作为生物标记物为环境可持续发展铺路。综述了元蛋白质组学的发展概况及其在微生物功能研究中的重大作用,强调了元蛋白质组学方法在分析新功能基因及其相关基因,揭示微生物多样性与微生物群体功能之间的关系等方面起到的作用,并对其应用前景进行了展望。     

Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers

Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here, we describe epicPCR (Emulsion, Paired Isolation and Concatenation PCR), a new technique that links functional genes and phylogenetic markers in uncultured single cells, providing a throughput of hundreds of thousands of cells with costs comparable to one genomic library preparation. We demonstrate the utility of our technique in a natural environment by profiling a sulfate-reducing community in a freshwater lake, revealing both known sulfate reducers and discovering new putative sulfate reducers. Our method is adaptable to any conserved genetic trait and translates genetic associations from diverse microbial samples into a sequencing library that answers targeted ecological questions. Potential applications include identifying functional community members, tracing horizontal gene transfer networks and mapping ecological interactions between microbial cells.     

Definitions of enzyme function for the structural genomics era

Questions are being asked about how enzyme function is described at the molecular level and the strengths and weaknesses of the EC system for this purpose. A new approach to describing enzyme function has been proposed that might improve our capabilities for functional inference for members of enzyme superfamilies.     

Chemical ligation to obtain proteins comprising helices with individual amino acid sequences

Development of the strategies for assembling multiple kinds of peptide segments would give new possibilities for the de novo design of functional proteins. We will introduce our approach for the selective assembly of helical peptide segments on a peptide template to give four-helix-bundle proteins comprising individual helices.