Phenotypic Heterogeneity,a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Phenotypic heterogeneity describes the occurrence of “nonconformist” cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations.     

Identification, Mapping and Linkage Analysis of Randomly Amplified DNA Polymorphisms in Tetrahymena Thermophila

Using the random amplified polymorphic DNA (RAPD) technique and exploiting the unique genetics of Tetrahymena thermophila, we have identified and characterized 40 DNA polymorphisms occurring between two inbred strains (B and C3) of this ciliated protozoan. These RAPD markers permit the PCR amplification of a DNA species using template DNA from SB1969 (B strain) but fail to do so using DNA from C3-368-5 (C3 strain). Polymorphisms were mapped to chromosomes using a panel of monosomic strains constructed by crossing B strain-derived nullisomic strains to inbred strain C3. They map to all five chromosomes and appear to be evenly distributed throughout the genome. Chromosomal groups were then analyzed for linkage using meiotic segregants; four linkage groups were identified in chromosomes 1R, 2L, 3 and 5. The RAPD method appears useful for the construction of a genetic map of the Tetrahymena genome based on DNA polymorphisms.     

一种单核苷酸多态性的单倍型分析技术

运用多步PCR和测序技术,完成基因组中相距较远的单核苷酸多态位点的单倍型构建。通过设计2条等位基因特异性引物,扩增大片段DNA(10kb左右),以此大片段DNA作为下一轮PCR反应的模板,再在该片段中设计待检测区域的PCR引物,进行第2轮PCR。对PCR产物进行测序分析,确定其多态位点处的等位基因。结合第1轮PCR中的等位基因特异性引物,即可确定该大片段DNA中不同单核苷酸多态性构成的单倍型。以脂蛋白脂酶基因为例,应用其启动子区以及第4外显子区的等位基因特异性引物扩增约16kb的DNA片段,然后检测位于该片段中第2、3外显子的多态性。在￡-尸￡-基因第2内含子中发现了 13557G→A多态性。经分析确定出-421G／ 13557G／ 15222A、-421A／ 13557G／ 15222A、-421G／ 13557G／ 15222G、-421G／ 13557A／ 15222A等4种单倍型。等位基因特异性PCR结合小片段测序是一种快捷高效的对相距较远的多个SNP进行单倍型构建的新策略。     

Patient Identification for Computer Data Linkage

To permit linkage of computerized patient data obtained from different sources, a universal and efficient method of patient identification is necessary. A coding system of 16 characters with a high degree of discrimination is proposed. The first five characters code the individual''s family name, the next four his given name; the next six digits are his date of birth expressed in day, month and year; and the last character codes his sex. This system, using readily available patient information, is simple to manipulate and generates codes that are also medically informative. When this method of identification was tested on a list of 18,000 persons, no identical codes were found.     

Linkage Disequilibrium Analysis of Chromosomal Inversion Polymorphisms of Drosophila

The linkage disequilibrium pattern analysis is a method that allows one to detect present and past events of selection. We applied it to our data on the inversions of Drosophila mediopunctata and to published data of Drosophila subobscura, which are systems probably under complex modes of selection. The method gave meaningful results showing that it might be an excellent exploratory tool to identify problems worthy of further study. It is also suggested that it can be used as a criterion to determine the roots of inversion phylogenies.     

Identification of Single Nucleotide Polymorphisms and Analysis of Linkage Disequilibrium in Different Bamboo Species Using the Candidate Gene Approach

Bamboos are one of the most beautiful and useful plants on Earth. The genetic background and population structure of bamboos are well known, which helps accelerate the process of artificial domestication of bamboo. Partial sequences of six genes involved in nitrogen use efficiency in 32 different bamboo species were analyzed for occurrence of single nucleotide polymorphisms (SNPs). The nucleotide diversity θw and total nucleotide polymorphisms π_T of the sequenced DNA regions was 0.05137 and 0.03332, respectively. Both πnonsyn /πsyn and Ka/Ks values were <1. The nucleotide sequences of these six genes were inferred to be relatively conserved, and the haplotype diversity was relatively high. The results of evolutionary neutrality tests showed that the six genes were in line with neutral evolution, and that the NRT2.1 and AMT2.1 gene sequences may have experienced negative selection. An inter-SNP recombination event at the NRT2.1 gene in the all pooled sample, of all 32 bamboo species was the lowest at 0.0645, whereas the AMT gene recombination events were all >0.1. Estimation and analysis of linkage disequilibrium of five genes revealed that with the increase in nucleotide sequence length, the degree of SNP linkage disequilibrium decreased rapidly. We inferred the population genetic structure of 32 bamboo species based on the SNP loci of six genes with frequencies >18%. 32 bamboo species were divided into five categories, which indicated that the combined population of all bamboo species had obvious multivariate characteristics and was heterogeneous; red (Group 1) and green (Group 2) were the main groups.     

构建分子标记连锁图谱的一种新方法：三点自交法

作者从数学上导出了基因作图的三点自交方法。这一方法同用三点测交法一样能提供各种作图信息,但不需要选育三隐性纯合基因亲本或品系,因而能大大提高作图功效。,从理论上证明,该方法也适合于小群体作图分子标记连锁图谱,同时用Ｆisher单一观察信息（即Ｆ信息）量证明,三点自交法是一种有效的作图方法,应用ＭＡＰＭＡＫＥＲ程序中所提供的才鼠Ｆ２群体中３３３个个体的１２个ＲＦＬＰ标记位点中前６个位点的数据对三点自交图图距计算具有与ＭＡＰＭＡＫＥＲ程序一样的功能,而且还提供了位点间的交叉干涉和位点的相引或相斥构型等信息以及紧密位点间发生负干涉作用的证据。     

A Simple Method for Testing Monthly Statistical Rates for Normalization

The spectral analysis of birth statistics, expressed in monthly rates, shows a strong periodic component even if a single child is born every day of the year. This is, of course, due to the different number of days per month. Most human or animal statistics as well as agricultural and biometeorological variables are only available as monthly, and not daily rates or values. If spectral components of time series are of interest, it is necessary to normalize monthly rates. This necessity has been a pre-analytical routine for quite some time, and various methods of normalization are described in the literature (1,3,7): the rates are either expressed as the daily mean within a month or as rates of normalized months with 31, 30 or 30.4 days (the latter results in a 365-day year). Each of the different methods leads to the same result, if the analysis can be based on relative deviations from the mean.

In the majority of the statistical material, the chosen method of normalization is clearly stated. But if a study tries to cover many different statistical populations and as many years as possible, the statistical material is often based on several (partly secondary) sources and photocopied extracts from large volumes. This can lead to confusion whether the used statistics contain normalized or crude original monthly rates.     

Meta-Regression Analyses to Explain Statistical Heterogeneity in a Systematic Review of Strategies for Guideline Implementation in Primary Health Care

This study is an in-depth-analysis to explain statistical heterogeneity in a systematic review of implementation strategies to improve guideline adherence of primary care physicians in the treatment of patients with cardiovascular diseases. The systematic review included randomized controlled trials from a systematic search in MEDLINE, EMBASE, CENTRAL, conference proceedings and registers of ongoing studies. Implementation strategies were shown to be effective with substantial heterogeneity of treatment effects across all investigated strategies. Primary aim of this study was to explain different effects of eligible trials and to identify methodological and clinical effect modifiers. Random effects meta-regression models were used to simultaneously assess the influence of multimodal implementation strategies and effect modifiers on physician adherence. Effect modifiers included the staff responsible for implementation, level of prevention and definition pf the primary outcome, unit of randomization, duration of follow-up and risk of bias. Six clinical and methodological factors were investigated as potential effect modifiers of the efficacy of different implementation strategies on guideline adherence in primary care practices on the basis of information from 75 eligible trials. Five effect modifiers were able to explain a substantial amount of statistical heterogeneity. Physician adherence was improved by 62% (95% confidence interval (95% CI) 29 to 104%) or 29% (95% CI 5 to 60%) in trials where other non-medical professionals or nurses were included in the implementation process. Improvement of physician adherence was more successful in primary and secondary prevention of cardiovascular diseases by around 30% (30%; 95% CI -2 to 71% and 31%; 95% CI 9 to 57%, respectively) compared to tertiary prevention. This study aimed to identify effect modifiers of implementation strategies on physician adherence. Especially the cooperation of different health professionals in primary care practices might increase efficacy and guideline implementation seems to be more difficult in tertiary prevention of cardiovascular diseases.     

A Robust Statistical Method for Detecting Differentially Expressed Genes

DNA microarray technology allows researchers to monitor the expressions of thousands of genes under different conditions, and to measure the levels of thousands of different DNA molecules at a given point in the life of an organism, tissue or cell. A wide variety of different diseases that are characterised by unregulated gene expression, DNA replication, cell division and cell death, can be detected early using microarrays. One of the major objectives of microarray experiments is to identify differentially expressed genes under various conditions. The detection of differential gene expression under two different conditions is very important in biological studies, and allows us to identify experimental variables that affect different biological processes. Most of the tests available in the literature are based on the assumption of normal distribution. However, the assumption of normality may not be true in real-life data, particularly with respect to microarray data.A test is proposed for the identification of differentially expressed genes in replicated microarray experiments conducted under two different conditions. The proposed test does not assume the distribution of the parent population; thus, the proposed test is strictly nonparametric in nature. We calculate the p-value and the asymptotic power function of the proposed test statistic. The proposed test statistic is compared with some of its competitors under normal, gamma and exponential population setup using the Monte Carlo simulation technique. The application of the proposed test statistic is presented using microarray data. The proposed test is robust and highly efficient when populations are non-normal.     

基于贝叶斯统计的遗传连锁分析方法

贝叶斯学派是不同于经典数理统计的一个重要学派, 其发展的贝叶斯统计方法在现代科学的许多领域已有着广泛的应用。探讨了贝叶斯统计在遗传连锁分析中的应用, 包括遗传重组率的贝叶斯估计、遗传连锁的贝叶斯因子检验和基于马尔可夫链蒙特卡罗理论的遗传连锁图谱构建。用编制的SAS/IML程序进行了模拟研究和实例分析, 验证了贝叶斯方法在遗传连锁分析中的有效性和实用性。     

Operationalising Factors That Explain the Emergence of Infectious Diseases: A Case Study of the Human Campylobacteriosis Epidemic

A framework of general factors for infectious disease emergence was made operational for Campylobacter utilising explanatory variables including time series and risk factor data. These variables were generated using a combination of empirical epidemiology, case-case and case-control studies, time series analysis, and microbial sub-typing (source attribution, diversity, genetic distance) to unravel the changing/emerging aetiology of human campylobacteriosis. The study focused on Scotland between 1990–2012 where there was a 75% increase in reported cases that included >300% increase in the elderly and 50% decrease in young children. During this period there were three phases 1990–2000 a 75% rise and a 20% fall to 2006, followed by a 19% resurgence. The rise coincided with expansions in the poultry industry, consumption of chicken, and a shift from rural to urban cases. The post-2000 fall occurred across all groups apart from the elderly and coincided with a drop of the prevalence of Campylobacter in chicken and a higher proportion of rural cases. The increase in the elderly was associated with uptake of proton pump inhibitors. During the resurgence the increase was predominantly in adults and the elderly, again there was increasing use of PPIs and high prevalences in chicken and ruminants. Cases associated with foreign travel during the study also increased from 9% to a peak of 16% in 2006 before falling to an estimated 10% in 2011, predominantly in adults and older children. During all three periods source attribution, genetic distance, and diversity measurements placed human isolates most similar to those in chickens. A combination of emergence factors generic for infectious diseases were responsible for the Campylobacter epidemic. It was possible to use these to obtain a putative explanation for the changes in human disease and the potential to make an informed view of how incidence rates may change in the future.     

A Maximum Likelihood Method for Estimating Genome Length Using Genetic Linkage Data

The genetic length of a genome, in units of Morgans or centimorgans, is a fundamental characteristic of an organism. We propose a maximum likelihood method for estimating this quantity from counts of recombinants and nonrecombinants between marker locus pairs studied from a backcross linkage experiment, assuming no interference and equal chromosome lengths. This method allows the calculation of the standard deviation of the estimate and a confidence interval containing the estimate. Computer simulations have been performed to evaluate and compare the accuracy of the maximum likelihood method and a previously suggested method-of-moments estimator. Specifically, we have investigated the effects of the number of meioses, the number of marker loci, and variation in the genetic lengths of individual chromosomes on the estimate. The effect of missing data, obtained when the results of two separate linkage studies with a fraction of marker loci in common are pooled, is also investigated. The maximum likelihood estimator, in contrast to the method-of-moments estimator, is relatively insensitive to violation of the assumptions made during analysis and is the method of choice. The various methods are compared by application to partial linkage data from Xiphophorus.     

Modification of a Rapid Method for the Identification of Gene-Specific Polymorphisms in Cryptosporidium parvum and Its Application to Clinical and Epidemiological Investigations

The application of genotyping to clinical isolates of Cryptosporidium has increased significantly our knowledge and understanding of the distribution and epidemiology of this parasite. However, some methods can be laborious and demand specialist technical expertise. PCR-restriction fragment length polymorphism (RFLP) techniques represent a more rapid and simple method of genotyping to support epidemiological and clinical investigations than conventional DNA analytical techniques. We describe a nested PCR-RFLP technique that identifies polymorphisms in the C. parvum thrombospondin-related adhesive protein gene locus; this method offers a sensitive and specific tool for the confirmation and investigation of disease associated with C. parvum. The potential of this enhanced method is demonstrated by its application to the confirmation and epidemiological investigation of an outbreak of cryptosporidiosis associated with a school visit to an open farm.     

Identification of Allelic Imbalance with a Statistical Model for Subtle Genomic Mosaicism

Genetic heterogeneity in a mixed sample of tumor and normal DNA can confound characterization of the tumor genome. Numerous computational methods have been proposed to detect aberrations in DNA samples from tumor and normal tissue mixtures. Most of these require tumor purities to be at least 10–15%. Here, we present a statistical model to capture information, contained in the individual''s germline haplotypes, about expected patterns in the B allele frequencies from SNP microarrays while fully modeling their magnitude, the first such model for SNP microarray data. Our model consists of a pair of hidden Markov models—one for the germline and one for the tumor genome—which, conditional on the observed array data and patterns of population haplotype variation, have a dependence structure induced by the relative imbalance of an individual''s inherited haplotypes. Together, these hidden Markov models offer a powerful approach for dealing with mixtures of DNA where the main component represents the germline, thus suggesting natural applications for the characterization of primary clones when stromal contamination is extremely high, and for identifying lesions in rare subclones of a tumor when tumor purity is sufficient to characterize the primary lesions. Our joint model for germline haplotypes and acquired DNA aberration is flexible, allowing a large number of chromosomal alterations, including balanced and imbalanced losses and gains, copy-neutral loss-of-heterozygosity (LOH) and tetraploidy. We found our model (which we term J-LOH) to be superior for localizing rare aberrations in a simulated 3% mixture sample. More generally, our model provides a framework for full integration of the germline and tumor genomes to deal more effectively with missing or uncertain features, and thus extract maximal information from difficult scenarios where existing methods fail.