A quantitative account of genomic island acquisitions in prokaryotes

<p>Abstract</p> <p>Background</p> <p>Microbial genomes do not merely evolve through the slow accumulation of mutations, but also, and often more dramatically, by taking up new DNA in a process called horizontal gene transfer. These innovation leaps in the acquisition of new traits can take place via the introgression of single genes, but also through the acquisition of large gene clusters, which are termed Genomic Islands. Since only a small proportion of all the DNA diversity has been sequenced, it can be hard to find the appropriate donors for acquired genes via sequence alignments from databases. In contrast, relative oligonucleotide frequencies represent a remarkably stable genomic signature in prokaryotes, which facilitates compositional comparisons as an alignment-free alternative for phylogenetic relatedness.</p> <p>In this project, we test whether Genomic Islands identified in individual bacterial genomes have a similar genomic signature, in terms of relative dinucleotide frequencies, and can therefore be expected to originate from a common donor species.</p> <p>Results</p> <p>When multiple Genomic Islands are present within a single genome, we find that up to 28% of these are compositionally very similar to each other, indicative of frequent recurring acquisitions from the same donor to the same acceptor.</p> <p>Conclusions</p> <p>This represents the first quantitative assessment of common directional transfer events in prokaryotic evolutionary history. We suggest that many of the resident Genomic Islands per prokaryotic genome originated from the same source, which may have implications with respect to their regulatory interactions, and for the elucidation of the common origins of these acquired gene clusters.</p

Bronnen van antibioticaresistentie in het milieu en mogelijke maatregelen

Het RIVM heeft in samenwerking met andere instituten onderzocht hoeveel resistente bacteriën via afvalwater in het Nederlandse oppervlaktewater terechtkomen. Afvalwater is, naast mest, de belangrijkste bron waardoor antibioticaresistente bacteriën in het milieu belanden. In 60 tot 100% van het onderzochte afvalwater zitten bijzonder resistente micro-organismen(BMRO), zoals ESBL-producerende E. coli en carbapenemresistente Enterobacteriaceae. Daarnaast zijn resten van antibiotica in het afvalwater gevonden. Mensen kunnen aan resistente bacteriën in het milieu worden blootgesteld, bijvoorbeeld als zij in contact komen met water waarop gezuiverd afvalwater wordt geloosd. Vooralsnog is het onduidelijk hoe groot de bijdrage van deze blootstelling is ten opzichte van andere blootstellingsroutes, en wat de gevolgen daarvan voor de volksgezondheid zijn. Daarvoor wordt aanvullend onderzoek aanbevolen. Duidelijk is wel dat mensen naast blootstelling via het milieu, ook door andere bronnen kunnen worden blootgesteld aan antibioticaresistente bacteriën, bijvoorbeeld tijdens reizen naar landen in Azië of Zuid-Amerika. Door de huidige behandeling van afvalwater nemen de concentraties van antibioticaresistente bacteriën af. Er bestaan aanvullende zuiveringstechnieken voor afvalwater die het aantal antibioticaresistente bacteriën in het oppervlaktewater nog verder kunnen verminderen. Ook de concentraties van resistente bacteriën in mest kunnen door aanvullende zuiveringstechnieken verminderd worden.In collaboration with other institu tions , RIVM investigated how many resistant bacteria enter Dutch surface water s from waste water treatment plants. Next to manure, waste water is the main source of resistant bacteria in the environment. Resistant bacteria of particular public health concern, including ESBL -producing E. coli and carbapenem resistant Enterobacteriace ae, have been found in 60 -100% of all investigated waste water samples. Antibiotics themselves have also been found in waste water. Human exposure to resistant bacteria is possible, for example, upon contact with surface water which receives waste water treatment plant effluent. So far, the contribution of this exposure to the total exposure to resistant bacteria is unknown, as are the effects of this exposure on public health. Additional research is therefore recommended. Humans can also be exposed to resistant bacteria via other routes, such as travel to Asian or Latin American. The current treatment of waste water reduces the concen trations of resistant bacteria. Advanced techniques are available which can decrease the amounts of resistant bacteria further. Options for the reduction of resistant bacteria also exist for the treatment of manure

Proteomic Analysis of the Secretory Response of Aspergillus niger to D-Maltose and D-Xylose

Fungi utilize polysaccharide substrates through extracellular digestion catalyzed by secreted enzymes. Thus far, protein secretion by the filamentous fungus Aspergillus niger has mainly been studied at the level of individual proteins and by genome and transcriptome analyses. To extend these studies, a complementary proteomics approach was applied with the aim to investigate the changes in secretome and microsomal protein composition resulting from a shift to a high level secretion condition. During growth of A. niger on d-sorbitol, small amounts of d-maltose or d-xylose were used as inducers of the extracellular amylolytic and xylanolytic enzymes. Upon induction, protein compositions in the extracellular broth as well as in enriched secretory organelle (microsomal) fractions were analyzed using a shotgun proteomics approach. In total 102 secreted proteins and 1,126 microsomal proteins were identified in this study. Induction by d-maltose or d-xylose resulted in the increase in specific extracellular enzymes, such as glucoamylase A on d-maltose and β-xylosidase D on d-xylose, as well as of microsomal proteins. This reflects the differential expression of selected genes coding for dedicated extracellular enzymes. As expected, the addition of extra d-sorbitol had no effect on the expression of carbohydrate-active enzymes, compared to addition of d-xylose or d-maltose. Furthermore, d-maltose induction caused an increase in microsomal proteins related to translation (e.g., Rpl15) and vesicular transport (e.g., the endosomal-cargo receptor Erv14). Millimolar amounts of the inducers d-maltose and d-xylose are sufficient to cause a direct response in specific protein expression levels. Also, after induction by d-maltose or d-xylose, the induced enzymes were found in microsomes and extracellular. In agreement with our previous findings for d-xylose induction, d-maltose induction leads to recruitment of proteins involved in proteasome-mediated degradation

N-gram analysis of 970 microbial organisms reveals presence of biological language models

<p>Abstract</p> <p>Background</p> <p>It has been suggested previously that genome and proteome sequences show characteristics typical of natural-language texts such as "signature-style" word usage indicative of authors or topics, and that the algorithms originally developed for natural language processing may therefore be applied to genome sequences to draw biologically relevant conclusions. Following this approach of 'biological language modeling', statistical n-gram analysis has been applied for comparative analysis of whole proteome sequences of 44 organisms. It has been shown that a few particular amino acid n-grams are found in abundance in one organism but occurring very rarely in other organisms, thereby serving as genome signatures. At that time proteomes of only 44 organisms were available, thereby limiting the generalization of this hypothesis. Today nearly 1,000 genome sequences and corresponding translated sequences are available, making it feasible to test the existence of biological language models over the evolutionary tree.</p> <p>Results</p> <p>We studied whole proteome sequences of 970 microbial organisms using n-gram frequencies and cross-perplexity employing the Biological Language Modeling Toolkit and Patternix Revelio toolkit. Genus-specific signatures were observed even in a simple unigram distribution. By taking statistical n-gram model of one organism as reference and computing cross-perplexity of all other microbial proteomes with it, cross-perplexity was found to be predictive of branch distance of the phylogenetic tree. For example, a 4-gram model from proteome of <it>Shigellae flexneri 2a</it>, which belongs to the <it>Gammaproteobacteria </it>class showed a self-perplexity of 15.34 while the cross-perplexity of other organisms was in the range of 15.59 to 29.5 and was proportional to their branching distance in the evolutionary tree from <it>S. flexneri</it>. The organisms of this genus, which happen to be pathotypes of <it>E.coli</it>, also have the closest perplexity values with <it>E. coli.</it></p> <p>Conclusion</p> <p>Whole proteome sequences of microbial organisms have been shown to contain particular n-gram sequences in abundance in one organism but occurring very rarely in other organisms, thereby serving as proteome signatures. Further it has also been shown that perplexity, a statistical measure of similarity of n-gram composition, can be used to predict evolutionary distance within a genus in the phylogenetic tree.</p

Independent evolution of the core and accessory gene sets in the genus Neisseria: insights gained from the genome of Neisseria lactamica isolate 020-06

<p>Abstract</p> <p>Background</p> <p>The genus <it>Neisseria </it>contains two important yet very different pathogens, <it>N. meningitidis </it>and <it>N. gonorrhoeae</it>, in addition to non-pathogenic species, of which <it>N. lactamica </it>is the best characterized. Genomic comparisons of these three bacteria will provide insights into the mechanisms and evolution of pathogenesis in this group of organisms, which are applicable to understanding these processes more generally.</p> <p>Results</p> <p>Non-pathogenic <it>N. lactamica </it>exhibits very similar population structure and levels of diversity to the meningococcus, whilst gonococci are essentially recent descendents of a single clone. All three species share a common core gene set estimated to comprise around 1190 CDSs, corresponding to about 60% of the genome. However, some of the nucleotide sequence diversity within this core genome is particular to each group, indicating that cross-species recombination is rare in this shared core gene set. Other than the meningococcal <it>cps </it>region, which encodes the polysaccharide capsule, relatively few members of the large accessory gene pool are exclusive to one species group, and cross-species recombination within this accessory genome is frequent.</p> <p>Conclusion</p> <p>The three <it>Neisseria </it>species groups represent coherent biological and genetic groupings which appear to be maintained by low rates of inter-species horizontal genetic exchange within the core genome. There is extensive evidence for exchange among positively selected genes and the accessory genome and some evidence of hitch-hiking of housekeeping genes with other loci. It is not possible to define a 'pathogenome' for this group of organisms and the disease causing phenotypes are therefore likely to be complex, polygenic, and different among the various disease-associated phenotypes observed.</p

Mainstreams of Horizontal Gene Exchange in Enterobacteria: Consideration of the Outbreak of Enterohemorrhagic E. coli O104:H4 in Germany in 2011

Escherichia coli O104:H4 caused a severe outbreak in Europe in 2011. The strain TY-2482 sequenced from this outbreak allowed the discovery of its closest relatives but failed to resolve ways in which it originated and evolved. On account of the previous statement, may we expect similar upcoming outbreaks to occur recurrently or spontaneously in the future? The inability to answer these questions shows limitations of the current comparative and evolutionary genomics methods.status: publishe

Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent

Commensal bacteria often have an especially rich source of glycan-degrading enzymes which allow them to utilize undigested carbohydrates from the food or the host. The species Ruminococcus gnavus is present in the digestive tract of ≥90% of humans and has been implicated in gut-related diseases such as inflammatory bowel diseases (IBD). Here we analysed the ability of two R. gnavus human strains, E1 and ATCC 29149, to utilize host glycans. We showed that although both strains could assimilate mucin monosaccharides, only R. gnavus ATCC 29149 was able to grow on mucin as a sole carbon source. Comparative genomic analysis of the two R. gnavus strains highlighted potential clusters and glycoside hydrolases (GHs) responsible for the breakdown and utilization of mucin-derived glycans. Transcriptomic and functional activity assays confirmed the importance of specific GH33 sialidase, and GH29 and GH95 fucosidases in the mucin utilisation pathway. Notably, we uncovered a novel pathway by which R. gnavus ATCC 29149 utilises sialic acid from sialylated substrates. Our results also demonstrated the ability of R. gnavus ATCC 29149 to produce propanol and propionate as the end products of metabolism when grown on mucin and fucosylated glycans. These new findings provide molecular insights into the strain-specificity of R. gnavus adaptation to the gut environment advancing our understanding of the role of gut commensals in health and disease

A Benchmark of Parametric Methods for Horizontal Transfers Detection

Horizontal gene transfer (HGT) has appeared to be of importance for prokaryotic species evolution. As a consequence numerous parametric methods, using only the information embedded in the genomes, have been designed to detect HGTs. Numerous reports of incongruencies in results of the different methods applied to the same genomes were published. The use of artificial genomes in which all HGT parameters are controlled allows testing different methods in the same conditions. The results of this benchmark concerning 16 representative parametric methods showed a great variety of efficiencies. Some methods work very poorly whatever the type of HGTs and some depend on the conditions or on the metrics used. The best methods in terms of total errors were those using tetranucleotides as criterion for the window methods or those using codon usage for gene based methods and the Kullback-Leibler divergence metric. Window methods are very sensitive but less specific and detect badly lone isolated gene. On the other hand gene based methods are often very specific but lack of sensitivity. We propose using two methods in combination to get the best of each category, a gene based one for specificity and a window based one for sensitivity