细菌中整合性接合元件的研究进展

整合性接合元件是近年来在细菌中发现的一种可移动的基因元件,它位于染色体上,可通过接合转移的方式介导细菌间基因的水平转移。这种基因的水平转移有助于细菌适应特定的环境条件,但许多整合性接合元件包含耐药基因,这些遗传元件的水平转移极大地加速了耐药基因在同种及不同种属之间的传播,造成细菌的耐药以至多重耐药问题日益严重,耐药机制日趋复杂;同时整合性接合元件与基因岛有着密切的联系,因此对其特征及转移机制进行研究很有必要。     

致病菌基因组岛的研究进展

细菌基因组岛是细菌基因组上的特定区域,和水平基因转移相关,具有一定的结构特点,常携带致病、耐药及与适应性等功能相关的基因。通过基因组岛在细菌间的移动,可以造成相关基因在细菌间的传播,在细菌生存和致病等过程中具有重要作用。目前已经可通过生物信息和分子生物学实验等方法对基因组岛进行预测和验证。通过对致病菌基因组岛的研究,可以阐释细菌致病性和耐药等重要功能的获得,对疾病进行溯源,在传染病预防控制中具有重要意义。     

整合子基因盒系统及β-内酰胺酶介导的细菌耐药

整合子是一个能捕获并整合细胞外游离基因盒,并可使之转化为功能性基因的新型DNA元件。这种可移动的基因元件通过水平基因转移的方式极大地加速了抗性基因在同种及不同种属之间的传播,造成细菌的耐药以至多重耐药问题日益严重,耐药机制日趋复杂。尤其对临床上使用较多的头孢菌素类、青霉素类等β-内酰胺类抗生素的耐药,已给人类健康造成巨大威胁,急需阐明其复杂的耐药机制。     

细菌遗传元件水平转移与抗生素抗性研究进展*

细菌可移动遗传元件包括噬菌体、质粒、转座子、插入序列、整合子、基因组岛(genomic island and genomic islet)等,其中接合性质粒、转座子、整合子及基因组岛等是与抗生素抗性有关的元件,可以在同种甚至于不同种菌株间水平转移,加速了临床上耐药及多重耐药菌株的产生。综述了细菌与抗生素抗性有关的可移动遗传元件的种类、特征及转移机制的研究进展。     

细菌遗传元件水平转移与抗生素抗性研究进展

细菌可移动遗传元件包括噬菌体、质粒、转座子、插入序列、整合子、基因组岛（genomic island and genomic islet）等,其中接合性质粒、转座子、整合子及基因组岛等是与抗生素抗性有关的元件,可以在向种甚至于不同种菌株间水平转移,加速了临床上耐药及多重耐药菌株的产生。综述了细菌与抗生素抗性有关的可移动遗传元件的种类、特征及转移机制的研究进展。     

整合性接合元件SXT-R391分子生物学特性及其转移系统的研究进展

整合性接合元件(Integrative and conjugative elements,ICEs)主要介导原核生物间遗传信息的横向基因交换,在细菌毒性、耐药性、抗重金属等特性传播上发挥关键作用。ICEs的水平转移极大地加速了抗性基因在同种及不同种属之间的传播,造成细菌的耐药以至多重耐药问题日益严重,耐药机制日趋复杂;同时ICEs的接合转移过程受细菌Ⅳ型分泌系统(Type Ⅳ secretion system,T4SS)影响。本文着重从ICEs的基因结构、接合转移过程以及T4SS组成元件的结构进行概述,并对T4SS各组件间相互作用的研究进展进行了初步探讨。     

细菌自然转化的机制及影响因素

水平基因转移对耐药基因传播、编码毒素基因质粒的扩散和毒力岛的转移等过程具有重要的生物学意义。自然转化是指具有感受态的细菌从外界摄取并整合裸露DNA,是水平基因转移的方式之一。细菌发生自然转化极大地促进了耐药基因在不同细菌间的播散,导致细菌对抗生素耐药,给临床治疗带来极大的困难。许多细菌具备自然转化能力,但不同细菌自然转化过程存在着差异。细菌自然感受及转化的诱发及效率亦受到多种因素的影响。文中着重于阐述不同细菌的自然转化机制及其影响因素。     

奇异变形杆菌中基因岛介导的多重耐药传播研究进展

奇异变形杆菌是导致医院内感染的重要条件致病菌,广泛分布于自然环境及人和动物的肠道中。基因岛是细菌染色体上约10-200 kb独立的DNA片段,能促进宿主细菌适应复杂多变的环境,与细菌适应性进化密切相关。近年来在奇异变形杆菌基因组中发现了多个与多重耐药密切相关的基因岛,包括沙门菌基因岛1及其相关基因岛、SXT/R391整合性接合元件、PmGRI1等,表明基因岛在奇异变形杆菌多重耐药形成和传播中具有重要作用。本文对奇异变形杆菌中与耐药相关基因岛的结构特征、传播机制、流行情况等进行综述,以期为奇异变形杆菌中多重耐药相关基因岛的深入研究提供参考。     

水平基因转移介导抗菌素耐药性传播机制的研究进展

近几十年来,病原菌耐药性的出现和蔓延已上升为严峻的公共卫生问题。越来越多研究表明,抗菌素抗性基因(antibiotic resistance genes,ARGs)不仅仅见于临床所分离的病原体,而是包括所有的致病菌、共生菌以及环境中的细菌,它们都能在可移动遗传元件和噬菌体的作用下,通过水平基因转移(horizontal gene transfer,HGT)途径获得耐药性,进而形成抗菌素耐药基因簇(耐药基因组)。HGT可导致抗菌素的耐药性在环境共生菌和病原菌之间传播扩散,这可通过临床上一些重要的抗菌素耐药基因的传播证实。传统观念认为HGT的三种机制中,接合对ARGs的传播影响最大,最近研究表明转化和转导对ARGs播散起到不可忽视的作用。通过深入了解耐药基因组的传播及其在动员病原菌耐药中发挥的作用,对于控制这些基因的播散是至关重要的。将讨论耐药基因组的概念,提供临床相关的抗菌素抗性基因水平基因转移的例子,对当前已研究的促使抗菌素耐药性传播的各种HGT机制进行回顾。     

胁迫诱导抗性基因转移导致细菌耐药的分子机制研究进展

抗性基因转移是细菌形成耐药性的重要原因.近年来的研究表明胁迫因子可通过多种机制诱导抗性基因转移.DNA损伤可导致细菌产生SOS应激反应,进而诱导接合DNA介导的抗性基因转移.在一些缺乏SOS系统的细菌中,抗生素胁迫可诱导细菌建立自然转化感受态.此外,作者最近的研究表明普通胁迫应答因子RpoS调控一种由双链质粒DNA介导的固体基质表面的抗性基因转移方式.本文在总结SOS依赖和非依赖型胁迫因子诱导细菌接合和转化介导的DNA转移以及RpoS调控固体基质表面双链质粒DNA转移的基础上,提出今后需重点研究胁迫因子如何激活关键调控蛋白以及这些调控蛋白如何影响DNA转移相关基因表达等关键问题.解决上述问题将为寻找合适的分子靶标用于防控抗性基因转移导致的细菌耐药奠定基础.     

Interstrain transfer of the prophage ϕNM2 in staphylococcal strains

Staphylococcus aureus is a successful pathogen in part because the bacterium can adapt rapidly to selective pressures imparted by the external environment. Horizontal gene transfer (HGT) plays an integral role in the evolution of bacterial genomes, and phage transduction is likely to be the most common and important HGT mechanism for S. aureus. Phage can transfer not only its own genome DNA but also host bacterial DNA with or without pathogenicity islands to other bacteria. Here, we demonstrate that the staphylococcal prophage ?NM2 could transfer between strains Newman and NCTC8325/NCTC8325-4 by simulating a natural situation in laboratory without mitomycin C or ultra-violet light treatment. This transference may be caused by direct contact between Newman and NCTC8325/NCTC8325-4 instead of phage particles released in Newman culture’s supernatant. The rates of successful horizontal genetic transfer in recipients NCTC8325 and NCTC8325-4 were 2.1% and 1.8%, respectively. Prophage ?NM2 was integrated with one direction at an intergenic region between rpmF and isdB in all 17 lysogenic isolates. Phage particles were spontaneously released from lysogenic strains again and had no noticeable influence on the growth of host cells. The results reported herein provide insight into how mobile genetic elements such as prophages can lead to the emergence of genetic diversity among S. aureus strains.     

DNA methylation of mobile genetic elements in human cancers

Mobile genetic elements are responsible for half of the human genome, creating the host genomic instability or variability through several mechanisms. Two types of abnormal DNA methylation in the genome, hypomethylation and hypermethylation, are associated with cancer progression. Genomic hypermethylation has been most often observed on the CpG islands around gene promoter regions in cancer cells. In contrast, hypomethylation has been observed on mobile genetic elements in the cancer cells. It is recently considered that the hypomethylation of mobile genetic elements may play a biological role in cancer cells along with the DNA hypermethylation on CpG islands. Growing evidence has indicated that mobile genetic elements could be associated with the cancer initiation and progression through the hypomethylation. Here we review the recent progress on the relationship between DNA methylation and mobile genetic elements, focusing on the hypomethylation of LINE-1 and HERV elements in various human cancers and suggest that DNA hypomethylation of mobile genetic elements could have potential to be a new cancer therapy target in the future.     

Ecological fitness, genomic islands and bacterial pathogenicity. A Darwinian view of the evolution of microbes

The compositions of bacterial genomes can be changed rapidly and dramatically through a variety of processes including horizontal gene transfer. This form of change is key to bacterial evolution, as it leads to ‘evolution in quantum leaps’. Horizontal gene transfer entails the incorporation of genetic elements transferred from another organism—perhaps in an earlier generation—directly into the genome, where they form ‘genomic islands’, i.e. blocks of DNA with signatures of mobile genetic elements. Genomic islands whose functions increase bacterial fitness, either directly or indirectly, have most likely been positively selected and can be termed ‘fitness islands’. Fitness islands can be divided into several subtypes: ‘ecological islands’ in environmental bacteria and ‘saprophytic islands’, ‘symbiosis islands’ or ‘pathogenicity islands’ (PAIs) in microorganisms that interact with living hosts. Here we discuss ways in which PAIs contribute to the pathogenic potency of bacteria, and the idea that genetic entities similar to genomic islands may also be present in the genomes of eukaryotes.     

Pathogenicity islands: the tip of the iceberg.

Pathogenicity islands represent distinct genetic elements encoding virulence factors of pathogenic bacteria. Pathogenicity islands belong to the class of genomic islands, which are common genetic elements sharing a set of unifying features. Genomic islands have been acquired by horizontal gene transfer. In recent years many different genomic islands have been discovered in a variety of pathogenic as well as non-pathogenic bacteria. Because they promote genetic variability, genomic islands play an important role in microbial evolution.     

Staphylococcus aureus mobile genetic elements

Among the bacteria groups, most of them are known to be beneficial to human being whereas only a minority is being recognized as harmful. The pathogenicity of bacteria is due, in part, to their rapid adaptation in the presence of selective pressures exerted by the human host. In addition, through their genomes, bacteria are subject to mutations, various rearrangements or horizontal gene transfer among and/or within bacterial species. Bacteria’s essential metabolic functions are generally encoding by the core genes. Apart of the core genes, there are several number of mobile genetic elements (MGE) acquired by horizontal gene transfer that might be beneficial under certain environmental conditions. These MGE namely bacteriophages, transposons, plasmids, and pathogenicity islands represent about 15 % Staphylococcus aureus genomes. The acquisition of most of the MGE is made by horizontal genomic islands (GEI), recognized as discrete DNA segments between closely related strains, transfer. The GEI contributes to the wide spread of microorganisms with an important effect on their genome plasticity and evolution. The GEI are also involve in the antibiotics resistance and virulence genes dissemination. In this review, we summarize the mobile genetic elements of S. aureus.     

Sequence and functional analyses of Haemophilus spp. genomic islands

Background

A major part of horizontal gene transfer that contributes to the diversification and adaptation of bacteria is facilitated by genomic islands. The evolution of these islands is poorly understood. Some progress was made with the identification of a set of phylogenetically related genomic islands among the Proteobacteria, recognized from the investigation of the evolutionary origins of a Haemophilus influenzae antibiotic resistance island, namely ICEHin1056. More clarity comes from this comparative analysis of seven complete sequences of the ICEHin1056 genomic island subfamily.

Results

These genomic islands have core and accessory genes in approximately equal proportion, with none demonstrating recent acquisition from other islands. The number of variable sites within core genes is similar to that found in the host bacteria. Furthermore, the GC content of the core genes is similar to that of the host bacteria (38% to 40%). Most of the core gene content is formed by the syntenic type IV secretion system dependent conjugative module and replicative module. GC content and lack of variable sites indicate that the antibiotic resistance genes were acquired relatively recently. An analysis of conjugation efficiency and antibiotic susceptibility demonstrates that phenotypic expression of genomic island-borne genes differs between different hosts.

Conclusion

Genomic islands of the ICEHin1056 subfamily have a longstanding relationship with H. influenzae and H. parainfluenzae and are co-evolving as semi-autonomous genomes within the 'supragenomes' of their host species. They have promoted bacterial diversity and adaptation through becoming efficient vectors of antibiotic resistance by the recent acquisition of antibiotic resistance transposons.     

Horizontal gene transfers link a human MRSA pathogen to contagious bovine mastitis bacteria

Background

Acquisition of virulence factors and antibiotic resistance by many clinically important bacteria can be traced to horizontal gene transfer (HGT) between related or evolutionarily distant microflora. Comparative genomic analysis has become an important tool for identifying HGT DNA in emerging pathogens. We have adapted the multi-genome alignment tool EvoPrinter to facilitate discovery of HGT DNA sequences within bacterial genomes and within their mobile genetic elements.

Principal Findings

EvoPrinter analysis of 13 different Staphylococcus aureus genomes revealed that one of the human isolates, the hospital epidemic methicillin-resistant MRSA252 strain, uniquely shares multiple putative HGT DNA sequences with different causative agents of bovine mastitis that are not found in the other human S. aureus isolates. MRSA252 shares over 14 different DNA sequence blocks with the bovine mastitis ET3 S. aureus strain RF122, and many of the HGT DNAs encode virulence factors. EvoPrinter analysis of the MRSA252 chromosome also uncovered virulence-factor encoding HGT events with the genome of Listeria monocytogenes and a Staphylococcus saprophyticus associated plasmid. Both bacteria are also causal agents of contagious bovine mastitis.

Conclusions

EvoPrinter analysis reveals that the human MRSA252 strain uniquely shares multiple DNA sequence blocks with different causative agents of bovine mastitis, suggesting that HGT events may be occurring between these pathogens. These findings have important implications with regard to animal husbandry practices that inadvertently enhance the contact of human and livestock bacterial pathogens.     

A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns

Background  

Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level using computer software or hybridization analysis to compare different bacterial genomic sequences. We describe here a novel experimental approach to study the evolution of species-specific bacterial genomic islands that identifies island genes that have evolved in such a way that they are differentially-expressed depending on the bacterial host background into which they are transferred.     

Prediction of genomic islands in seven human pathogens using the Z-Island method

We adopted the method of Zhang and Zhang (the Z-Island method) to identify genomic islands in seven human pathogens, analyzing their chromosomal DNA sequences. The Z-Island method is a theoretical method for predicting genomic islands in bacterial genomes; it consists of determination of the cumulative GC profile and computation of codon usage bias. Thirty-one genomic islands were found in seven pathogens using this method. Further analysis demonstrated that most have the known conserved features; this increases the probability that they are real genomic islands. Eleven genomic islands were found to code for products involved in causing disease (virulence factors) or in resistance to antibiotics (resistance factors). This finding could be useful for research on the pathogenicity of these bacteria and helpful in the treatment of the diseases that they cause. In a comparison of the distribution of mobility elements in genomic islands predicted by different methods, the Z-Island method gave lower false-positive rates. The Z-Island method was found to detect more known genomic islands than the two methods that we compared it with, SIGI-HMM and IslandPick. Furthermore, it maintained a better balance between specificity and sensitivity. The only inconvenience is that the steps for finding genomic islands by the Z-Island method are semi-automatic.