Comparative Genomic Analyses of the Moraxella catarrhalis Serosensitive and Seroresistant Lineages Demonstrate Their Independent Evolution

Contains fulltext : 172169.pdf (publisher's version ) (Open Access)The bacterial speciesMoraxella catarrhalishas been hypothesized as being composed of two distinct lineages (referred to as the seroresistant [SR] and serosensitive [SS]) with separate evolutionary histories based on several molecular typing methods, whereas 16S ribotyping has suggested an additional split within the SS lineage. Previously, we characterized whole-genome sequences of 12 SR-lineage isolates, which revealed a relatively small supragenome when compared with other opportunistic nasopharyngeal pathogens, suggestive of a relatively short evolutionary history. Here, we performed whole-genome sequencing on 18 strains from both ribotypes of the SS lineage, an additional SR strain, as well as four previously identified highly divergent strains based on multilocus sequence typing analyses. All 35 strains were subjected to a battery of comparative genomic analyses which clearly show that there are three lineages-the SR, SS, and the divergent. The SR and SS lineages are closely related, but distinct from each other based on three different methods of comparison: Allelic differences observed among core genes; possession of lineage-specific sets of core and distributed genes; and by an alignment of concatenated core sequences irrespective of gene annotation. All these methods show that the SS lineage has much longer interstrain branches than the SR lineage indicating that this lineage has likely been evolving either longer or faster than the SR lineage. There is evidence of extensive horizontal gene transfer (HGT) within both of these lineages, and to a lesser degree between them. In particular, we identified very high rates of HGT between these two lineages for ss-lactamase genes. The four divergent strains aresui generis, being much more distantly related to both the SR and SS groups than these other two groups are to each other. Based on average nucleotide identities, gene content, GC content, and genome size, this group could be considered as a separate taxonomic group. The SR and SS lineages, although distinct, clearly form a single species based on multiple criteria including a large common core genome, average nucleotide identity values, GC content, and genome size. Although neither of these lineages arose from within the other based on phylogenetic analyses, the question of how and when these lineages split and then subsequently reunited in the human nasopharynx is explored

A publicly accessible database for Clostridioides difficile genome sequences supports tracing of transmission chains and epidemics

Clostridioides difficile is the primary infectious cause of antibiotic-associated diarrhea. Local transmissions and international outbreaks of this pathogen have been previously elucidated by bacterial whole-genome sequencing, but comparative genomic analyses at the global scale were hampered by the lack of specific bioinformatic tools. Here we introduce a publicly accessible database within EnteroBase (http://enterobase.warwick.ac.uk) that automatically retrieves and assembles C. difficile short-reads from the public domain, and calls alleles for core-genome multilocus sequence typing (cgMLST). We demonstrate that comparable levels of resolution and precision are attained by EnteroBase cgMLST and single-nucleotide polymorphism analysis. EnteroBase currently contains 18 254 quality-controlled C. difficile genomes, which have been assigned to hierarchical sets of single-linkage clusters by cgMLST distances. This hierarchical clustering is used to identify and name populations of C. difficile at all epidemiological levels, from recent transmission chains through to epidemic and endemic strains. Moreover, it puts newly collected isolates into phylogenetic and epidemiological context by identifying related strains among all previously published genome data. For example, HC2 clusters (i.e. chains of genomes with pairwise distances of up to two cgMLST alleles) were statistically associated with specific hospitals (P<10−4) or single wards (P=0.01) within hospitals, indicating they represented local transmission clusters. We also detected several HC2 clusters spanning more than one hospital that by retrospective epidemiological analysis were confirmed to be associated with inter-hospital patient transfers. In contrast, clustering at level HC150 correlated with k-mer-based classification and was largely compatible with PCR ribotyping, thus enabling comparisons to earlier surveillance data. EnteroBase enables contextual interpretation of a growing collection of assembled, quality-controlled C. difficile genome sequences and their associated metadata. Hierarchical clustering rapidly identifies database entries that are related at multiple levels of genetic distance, facilitating communication among researchers, clinicians and public-health officials who are combatting disease caused by C. difficile

A Novel Escherichia coli O157:H7 Clone Causing a Major Hemolytic Uremic Syndrome Outbreak in China

An Escherichia coli O157:H7 outbreak in China in 1999 caused 177 deaths due to hemolytic uremic syndrome. Sixteen outbreak associated isolates were found to belong to a new clone, sequence type 96 (ST96), based on multilocus sequence typing of 15 housekeeping genes. Whole genome sequencing of an outbreak isolate, Xuzhou21, showed that the isolate is phylogenetically closely related to the Japan 1996 outbreak isolate Sakai, both of which share the most recent common ancestor with the US outbreak isolate EDL933. The levels of IL-6 and IL-8 of peripheral blood mononuclear cells induced by Xuzhou21 and Sakai were significantly higher than that induced by EDL933. Xuzhou21 also induced a significantly higher level of IL-8 than Sakai while both induced similar levels of IL-6. The expression level of Shiga toxin 2 in Xuzhou21 induced by mitomycin C was 68.6 times of that under non-inducing conditions, twice of that induced in Sakai (32.7 times) and 15 times higher than that induced in EDL933 (4.5 times). Our study shows that ST96 is a novel clone and provided significant new insights into the evolution of virulence of E. coli O157:H7

Multilocus Sequence Typing as a Replacement for Serotyping in Salmonella enterica

Salmonella enterica subspecies enterica is traditionally subdivided into serovars by serological and nutritional characteristics. We used Multilocus Sequence Typing (MLST) to assign 4,257 isolates from 554 serovars to 1092 sequence types (STs). The majority of the isolates and many STs were grouped into 138 genetically closely related clusters called eBurstGroups (eBGs). Many eBGs correspond to a serovar, for example most Typhimurium are in eBG1 and most Enteritidis are in eBG4, but many eBGs contained more than one serovar. Furthermore, most serovars were polyphyletic and are distributed across multiple unrelated eBGs. Thus, serovar designations confounded genetically unrelated isolates and failed to recognize natural evolutionary groupings. An inability of serotyping to correctly group isolates was most apparent for Paratyphi B and its variant Java. Most Paratyphi B were included within a sub-cluster of STs belonging to eBG5, which also encompasses a separate sub-cluster of Java STs. However, diphasic Java variants were also found in two other eBGs and monophasic Java variants were in four other eBGs or STs, one of which is in subspecies salamae and a second of which includes isolates assigned to Enteritidis, Dublin and monophasic Paratyphi B. Similarly, Choleraesuis was found in eBG6 and is closely related to Paratyphi C, which is in eBG20. However, Choleraesuis var. Decatur consists of isolates from seven other, unrelated eBGs or STs. The serological assignment of these Decatur isolates to Choleraesuis likely reflects lateral gene transfer of flagellar genes between unrelated bacteria plus purifying selection. By confounding multiple evolutionary groups, serotyping can be misleading about the disease potential of S. enterica. Unlike serotyping, MLST recognizes evolutionary groupings and we recommend that Salmonella classification by serotyping should be replaced by MLST or its equivalents

A simple and intelligent routing and wavelength assignment algorithm for all-optical networks

In this paper we consider the routing and wavelength assignment problem in a wavelength routed all optical network. Inspired by techniques from artificial intelligence, in particular the Blocking Island (BI) abstraction, we propose a simple and intelligent routing and wavelength assignment (RWA) algorithm: BI_RWA. This algorithm can be used in arbitrarily connected optical networks. In addition, it is general enough such that with some simple modifications, it can be applied to different optical networking scenarios: static or dynamic traffic, single or multiple fiber links between node pairs, with or without wavelength converters. We have conducted simulation experiments to evaluate the performance of our algorithm. The simulation is carried out in two parts: static traffic and dynamic traffic. The results will demonstrate that our RWA algorithm outperforms state-of-the-art related algorithms

Integrated routing and grooming in GMPLS-based optical networks

This paper proposes an integrated routing and grooming algorithm for IP over WDM networks. Assuming a peer model in GMPLS-Based optical networks, we take into account the combined topology and resource usage information on both IP and WDM layers. Based on a clustering technique called Blocking Island Paradigm, we propose an enhanced Blocking Island Graph (BIG) network model with Blocking Island Hierarchy (BIH) to abstract network resources. The main idea of the algorithm is to keep the integrity and load balance of related Blocking Islands. We also combine a cost function in the routing algorithm to groom traffic flows into active lightpaths. The complexity of the algorithm is analyzed to show its efficiency. In the simulation, we compare the algorithm with three other integrated routing algorithms in terms of blocking probability. The three algorithms are: the integrated min-hop (IMH) routing algorithm, the maximum open capacity (MOCA) routing algorithm and the IP-WDM grooming (IWG) algorithm. Simulation results show our algorithm has the best performance.published_or_final_versio