Population proteomics: addressing protein diversity in humans

In the past several years, proteomics and its subdiscipline clinical proteomics have been engaged in the discovery of the next generation protein of biomarkers. As the effort and the intensive debate it has sparked continue, it is becoming apparent that a paradigm shift is needed in proteomics in order to truly comprehend the complexity of the human proteome and assess its subtle variations among individuals. This review introduces the concept of population proteomics as a future direction in proteomics research. Population proteomics is the study of protein diversity in human populations. High-throughput, top-down mass spectrometric approaches are employed to investigate, define and understand protein diversity and modulations across and within populations. Population proteomics is a discovery-oriented endeavor with a goal of establishing the incidence of protein structural variations and quantitative regulation of these modifications. Assessing human protein variations among and within populations is viewed as a paramount undertaking that can facilitate clinical proteomics’ effort in discovery and validation of protein features that can be used as markers for early diagnosis of disease, monitoring of disease progression and assessment of therapy. This review outlines the growing need for analyzing individuals’ proteomes and describes the approaches that are likely to be applied in such a population proteomics endeavor.     

Population proteomics: the concept, attributes, and potential for cancer biomarker research

This review outlines the concept of population proteomics and its implication in the discovery and validation of cancer-specific protein modulations. Population proteomics is an applied subdiscipline of proteomics engaging in the investigation of human proteins across and within populations to define and better understand protein diversity. Population proteomics focuses on interrogation of specific proteins from large number of individuals, utilizing top-down, targeted affinity mass spectrometry approaches to probe protein modifications. Deglycosylation, sequence truncations, side-chain residue modifications, and other modifications have been reported for myriad of proteins, yet little is know about their incidence rate in the general population. Such information can be gathered via population proteomics and would greatly aid the biomarker discovery efforts. Discovery of novel protein modifications is also expected from such large scale population proteomics, expanding the protein knowledge database. In regard to cancer protein biomarkers, their validation via population proteomics-based approaches is advantageous as mass spectrometry detection is used both in the discovery and validation process, which is essential for the detection of those structurally modified protein biomarkers.     

Population proteomics: investigation of protein diversity in human populations

Outlined in this review is the concept of population proteomics, its aspects, enabling approaches, and significance in understanding proteins' roles in physiological processes and diseases. Population proteomics addresses the need for individual assessment of proteins across large populations to delineate the existence of structural variations, determine their frequency, and explore the association of the modifications with specific diseases. Besides the basic concepts and underlying reasons for such protein diversity studies, also reviewed here are the results of two fundamental studies that investigated human plasma protein diversity across the healthy population in the United States. Such studies of protein diversity are needed to map all the post-expression protein modifications and determine the wild-type protein profiles, similar to the human diversity studies at the genome level that have helped redefine the "normal" human genome.     

Genetic diversity of the endangered species Rosa rugosa Thunb. in China and implications for conservation strategies

Rosa rugosa Thunb. is one of the dominant and important shrub species in estuary dunes and shingle beaches of northern China. However, its area of distribution, the number of populations, and the size of each population have decreased rapidly in the past two decades because of habitat degradation and loss. Random amplified polymorphic DNA markers were used to determine the genetic diversity of four remaining large natural populations of R. rugosa and to discuss an effective conservation strategy for this endangered species in China. High genetic variations were detected in R. rugosa populations in China. The mean percentage of polymorphic loci （P%） within four local populations was 57.99%, with the P% of the total population being 75.30%. Mean Shannon＇s information index （H0） was 0.2826, whereas total Ho was 0.3513. The genetic differentiation among populations was 0.1878, which indicates that most genetic diversity occurs within populations. Population Tumenjiang （TMJ） showed the highest genetic diversity （P% = 66.27%; H0 = 0.3117） and contained two exclusive bands. Population Changshandao （CSD） showed higher genetic diversity （P% =59.04%; H0 = 0.3065）. Populations TMJ and CSD contained 95.33% and 99.33%, respectively, of loci with moderate to high frequency （P〉0.05） of the total population. These results indicate that populations TMJ and CSD should be given priority for in situ conservation and regarded as seed or propagule sources for ex situ conservation. The results of the present study also suggest that R. rugosa in China has become endangered as a result of human actions rather than genetic depression of populations; thus, human interference should be absolutely forbidden in R. rugosa habitats.     

Proteomics in the post-genome age.

The genome sequencing effort has helped spawn the burgeoning field of proteomics. This review article examines state-of-the-art proteomics methods that are helping change the discovery paradigm in a variety of biological disciplines and, in particular, protein biochemistry. The review discusses both classical and novel methods to perform high-throughput qualitative and quantitative "global" as well as targeted proteome analysis of complex biological systems. From a drug discovery standpoint, the synergy between genomics and proteomics will help elucidate disease mechanisms, identify novel drug targets, and identify surrogate biomarkers that could be used to conduct clinical trials.     

Interactive proteomics: what lies ahead?

Interactive proteomics addresses the physical associations among proteins and establishes global, disease-, and pathway-specific protein interaction networks. The inherent chemical and structural diversity of proteins, their different expression levels, and their distinct subcellular localizations pose unique challenges for the exploration of these networks, necessitating the use of a variety of innovative and ingenious approaches. Consequently, recent years have seen exciting developments in protein interaction mapping and the establishment of very large interaction networks, especially in model organisms. In the near future, attention will shift to the establishment of interaction networks in humans and their application in drug discovery and understanding of diseases. In this review, we present an impressive toolbox of different technologies that we expect to be crucial for interactive proteomics in the coming years.     

野古草种群克隆的遗传变异和遗传结构

用酶电泳法和同工酶分析对东北松嫩草原西北部野古草种群克隆遗传变异性和种群遗传结构做了探讨。讨论了遗传多样性、地理距离和遗传距离之间的关系、大种群和小种群的遗传变异性和种群间的基因流 ;种群间 ,包括大种群和小种群间基因流、遗传和地理距离对遗传多样性的影响、昆虫和风传粉、种群籽苗的补充、遗传多样性的发生和保持 ,自交不亲和性和无性繁殖及体细胞突变     

A cytomic approach reveals population heterogeneity of Cupriavidus necator in response to harmful phenol concentrations

The understanding of functions of cells within microbial populations or communities is certainly needed for existing and novel cytomic approaches which grip the individual scale. Population behaviour results from single cell performances and is caused by the individual genetic pool, history, life cycle states and microenvironmental surroundings. Mimicking natural impaired environments, the paper shows that the Gram-negative Betaproteobacterium Cupriavidus necator dramatically altered its population heterogeneity in response to harmful phenol concentrations. Multiparametric flow cytometry was used to follow variations in structural cellular parameters like chromosome contents and storage materials. The functioning of these different cell types was resolved by ensuing proteomics after the cells' spatial separation by cell sorting, finding 11 proteins changed in their expression profile, among them elongation factor Tu and the trigger factor. At least one third of the individuals clearly underwent starving states; however, simultaneously these cells prepared themselves for entering the life cycle again. Using cytomics to recognise individual structure and function on the microbial scale represents an innovative technical design to describe the complexity of such systems, overcoming the disadvantage of small cell volumes and, thus, to resolve bacterial strategies to survive harmful environments by altering population heterogeneity.     

Applications of urinary proteomics in biomarker discovery

Urine is an important source of biomarkers. This article reviews current advances, major challenges, and future prospects in the field of urinary proteomics. Because the practical clinical problem is to distinguish diseases with similar symptoms, merely comparing samples from patients of a particular disease to those of healthy individuals is inadequate for finding biomarkers with sufficient diagnostic power. In addition, the variation of expression levels of urinary proteins among healthy individuals and individuals under different physiological conditions adds to the difficulty in identifying biomarkers. We propose that establishing the natural variation in urinary protein expression among a healthy population can serve as a reference to help identify protein abundance changes that are caused by disease, not by individual variations or physiological changes. We also discuss that comparing protein expression levels between urine and plasma may reveal the physiological function of the kidney and that may facilitate biomarker discovery. Finally, we propose that establishing a data-sharing platform for data collection and integrating results from all urinary biomarker studies will help promote the development of urinary proteomics.     

An overview of human protein databases and their application to functional proteomics in health and disease

Functional proteomics can be defined as a strategy to couple proteomic information with biochemical and physiological analyses with the aim of understanding better the functions of proteins in normal and diseased organs. In recent years, a variety of publicly available bioinformatics databases have been developed to support protein-related information management and biological knowledge discovery. In addition to being used to annotate the proteome, these resources also offer the opportunity to develop global approaches to the study of the functional role of proteins both in health and disease. Here, we present a comprehensive review of the major human protein bioinformatics databases. We conclude this review by discussing a few examples that illustrate the importance of these databases in functional proteomics research.     

Gene-expression variation within and among human populations

Understanding patterns of gene-expression variation within and among human populations will provide important insights into the molecular basis of phenotypic diversity and the interpretation of patterns of expression variation in disease. However, little is known about how gene-expression variation is apportioned within and among human populations. Here, we characterize patterns of natural gene-expression variation in 16 individuals of European and African ancestry. We find extensive variation in gene-expression levels and estimate that approximately 83% of genes are differentially expressed among individuals and that approximately 17% of genes are differentially expressed among populations. By decomposing total gene-expression variation into within- versus among-population components, we find that most expression variation is due to variation among individuals rather than among populations, which parallels observations of extant patterns of human genetic variation. Finally, we performed allele-specific quantitative polymerase chain reaction to demonstrate that cis-regulatory variation in the lymphocyte adaptor protein (SH2B adapter protein 3) contributes to differential expression between European and African samples. These results provide the first insight into how human population structure manifests itself in gene-expression levels and will help guide the search for regulatory quantitative trait loci.     

Biomedical applications of protein chips

The development of microchips involving proteins has accelerated within the past few years. Although DNA chip technologies formed the precedent, many different strategies and technologies have been used because proteins are inherently a more complex type of molecule. This review covers the various biomedical applications of protein chips in diagnostics, drug screening and testing, disease monitoring, drug discovery (proteomics), and medical research. The proteomics and drug discovery section is further subdivided to cover drug discovery tools (on-chip separations, expression profiling, and antibody arrays), molecular interactions and signaling pathways, the identification of protein function, and the identification of novel therapeutic compounds. Although largely focused on protein chips, this review includes chips involving cells and tissues as a logical extension of the type of data that can be generated from these microchips.     

Applications of cell-based phage display panning to proteomic analysis

In the post-genomic era, proteomics together with genomic tools have led to powerful new strategies in basic and clinical research. These combined “omics” technologies are being integrated into the drug target discovery process. Unlike the genome, the proteome is a highly dynamic entity that requires techniques capable of analyzing on selected populations of proteins in specific biological conditions that reflect the proteins’ functional characteristics. Antibodies have become one of the most important reagents for the analysis of selected populations of proteins, and the application of phage-display antibody libraries to high-throughput antibody generation against large numbers of various antigens provides a tool for proteome-wide protein expression analysis. In this review, we will discuss the utility of phage-display antibodies in proteomics applications, specifically for the discovery of novel disease markers and therapeutic targets.     

Species diversity and population density affect genetic structure and gene dispersal in a subtropical understory shrub

Aims The dispersal of pollen and seeds is spatially restricted and may vary among plant populations because of varying biotic interactions, population histories or abiotic conditions. Because gene dispersal is spatially restricted, it will eventually result in the development of spatial genetic structure (SGS), which in turn can allow insights into gene dispersal processes. Here, we assessed the effect of habitat characteristics like population density and community structure on small-scale SGS and estimate historical gene dispersal at different spatial scales.Methods In a set of 12 populations of the subtropical understory shrub Ardisia crenata, we assessed genetic variation at 7 microsatellite loci within and among populations. We investigated small-scale genetic structure with spatial genetic autocorrelation statistics and heterogeneity tests and estimated gene dispersal distances based on population differentiation and on within-population SGS. SGS was related to habitat characteristics by multiple regression.Important findings The populations showed high genetic diversity (H e = 0.64) within populations and rather strong genetic differentiation (F ′ ST = 0.208) among populations, following an isolation-by-distance pattern, which suggests that populations are in gene flow–drift equilibrium. Significant SGS was present within populations (mean Sp = 0.027). Population density and species diversity had a joint effect on SGS with low population density and high species diversity leading to stronger small-scale SGS. Estimates of historical gene dispersal from between-population differentiation and from within-population SGS resulted in similar values between 4.8 and 22.9 m. The results indicate that local-ranged pollen dispersal and inefficient long-distance seed dispersal, both affected by population density and species diversity, contributed to the genetic population structure of the species. We suggest that SGS in shrubs is more similar to that of herbs than to trees and that in communities with high species diversity gene flow is more restricted than at low species diversity. This may represent a process that retards the development of a positive species diversity–genetic diversity relationship.     

Isolation by distance and gene flow in the Eurasian badger (Meles meles) at both a local and broad scale

Eurasian badgers, Meles meles, have been shown to possess limited genetic population structure within Europe; however, field studies have detected high levels of philopatry, which are expected to increase population structure. Population structure will be a consequence of both contemporary dispersal and historical processes, each of which is expected to be evident at a different scale. Therefore, to gain a greater understanding of gene flow in the badger, we examined microsatellite diversity both among and within badger populations, focusing on populations from the British Isles and western Europe. We found that while populations differed in their allelic diversity, the British Isles displayed a similar degree of diversity to the rest of western Europe. The lower genetic diversity occurring in Ireland, Norway and Scotland was more likely to have resulted from founder effects rather than contemporary population density. While there was significant population structure (F ST = 0.19), divergence among populations was generally well explained by geographic distance (P < 0.0001) across the entire range studied of more than 3000 km. Transient effects from the Pleistocene appear to have been replaced by a strong pattern of genetic isolation by distance across western Europe, suggestive of colonization from a single refugium. Analysis of individuals within British populations through Mantel tests and spatial autocorrelation demonstrated that there was significant local population structure across 3-30 km, confirming that dispersal is indeed restricted. The isolation by distance observed among badger populations across western Europe is likely to be a consequence of this restricted local dispersal.     

Glycoscience aids in biomarker discovery

The glycome consists of all glycans (or carbohydrates) within a biological system, and modulates a wide range of important biological activities, from protein folding to cellular communications. The mining of the glycome for disease markers represents a new paradigm for biomarker discovery; however, this effort is severely complicated by the vast complexity and structural diversity of glycans. This review summarizes recent developments in analytical technology and methodology as applied to the fields of glycomics and glycoproteomics. Mass spectrometric strategies for glycan compositional profiling are described, as are potential refinements which allow structure-specific profiling. Analytical methods that can discern protein glycosylation at a specific site of modification are also discussed in detail. Biomarker discovery applications are shown at each level of analysis, highlighting the key role that glycoscience can play in helping scientists understand disease biology.     

Molecular evidence for historical and recent population size reductions of tiger salamanders (Ambystoma tigrinum) in Yellowstone National Park

Population declines caused by natural and anthropogenic factors can quickly erode genetic diversity in natural populations. In this study, we examined genetic variation within 10 tiger salamander populations across northern Yellowstone National Park in Wyoming and Montana, USA using eight microsatellite loci. We tested for the genetic signature of population decline using heterozygosity excess, shifts in allele frequencies, and low ratios of allelic number to allelic size range (M-ratios). We found different results among the three tests. All 10 populations had low M-ratios, five had shifts in allele frequencies and only two had significant heterozygosity excesses. These results support theoretical expectations of different temporal signatures among bottleneck tests and suggest that both historical fish stocking, recent, sustained drought, and possibly an emerging amphibian disease have contributed to declines in effective population size.     

Discovery of regulatory molecular events and biomarkers using 2D capillary chromatography and mass spectrometry

An important component of proteomic research is the high-throughput discovery of novel proteins and protein–protein interactions that control molecular events that contribute to critical cellular functions and human disease. The interactions of proteins are essential for cellular functions. Identifying perturbation of normal cellular protein interactions is vital for understanding the disease process and intervening to control the disease. A second area of proteomics research is the discovery of proteins that will serve as biomarkers for the early detection, diagnosis and drug treatment response for specific diseases. These studies have been referred to as clinical proteomics. To discover biomarkers, proteomics research employs the quantitative comparison of peptide and protein expression in body fluids and tissues from diseased individuals (case) versus normal individuals (control). Methods that couple 2D capillary liquid chromatography (LC) and tandem mass spectrometry (MS/MS) analysis have greatly facilitated this discovery science. Coupling 2D-LC/MS/MS analysis with automated genome-assisted spectra interpretation allows a direct, high-throughput and high-sensitivity identification of thousands of individual proteins from complex biological samples. The systematic comparison of experimental conditions and controls allows protein function or disease states to be modeled. This review discusses the different purification and quantification strategies that have been developed and used in combination with 2D-LC/MS/MS and computational analysis to examine regulatory protein networks and clinical samples.     

Integrating '-omics' and natural product discovery platforms to investigate metabolic exchange in microbiomes

The microbiome is an abundance of microorganisms within a host (e.g. human microbiome). These microorganisms produce small molecules and metabolites that have been shown to affect and dictate the physiology of an individual. Functional knowledge of these molecules, often produced for communication or defense, will reveal the interplay between microbes and host in health and disease. The vast diversity in structure and function of microbiome-associated small molecules necessitate tools that will utilize multiple '-omics' strategies to understand the interactions within the human microbiome. This review discusses the importance of these investigations and the integration of current '-omics' technologies with tools established in natural product discovery in order to identify and characterize uncharacterized small molecules in the effort towards diagnostic modeling of the human microbiome.