Estimating the association between antibiotic exposure and colonization with extended-spectrum ß-lactamase-producing Gram-negative bacteria using machine learning methods: a multicentre, prospective cohort study.

OBJECTIVES: The aim of the study was to measure the impact of antibiotic exposure on the acquisition of colonization with extended-spectrum ß-lactamase-producing Gram-negative bacteria (ESBL-GNB) accounting for individual- and group-level confounding using machine-learning methods. METHODS: Patients hospitalized between September 2010 and June 2013 at six medical and six surgical wards in Italy, Serbia and Romania were screened for ESBL-GNB at hospital admission, discharge, antibiotic start, and after 3, 7, 15 and 30 days. Primary outcomes were the incidence rate and predictive factors of new ESBL-GNB colonization. Random forest algorithm was used to rank antibiotics according to the risk of selection of ESBL-GNB colonization in patients not colonized before starting antibiotics. RESULTS: We screened 10 034 patients collecting 28 322 rectal swab samples. New ESBL-GNB colonization incidence with and without antibiotic treatment was 22/1000 and 9/1000 exposure-days, respectively. In the adjusted regression analyses, antibiotic exposure (hazard ratio (HR) 2.38; 95% CI 1.29-4.40), age 60-69 years (HR 1.19; 95% CI 1.05-1.34), and spring season (HR 1.25; 95% CI 1.14-1.38) were independently associated with new colonization. Monotherapy ranked higher als combination therapy in promoting ESBL-GNB colonization. Among monotherapy, cephalosporins ranked first followed by tetracycline (second), macrolide (fourth) and cotrimoxazole (seventh). Overall the ranking of cephalosporins was lower when used in combination. Among combinations not including cephalosporins, quinolones plus carbapenems ranked highest (eighth). Among sequential therapies, quinolones ranked highest (tenth) when prescribed within 30 days of therapy with cephalosporins. CONCLUSIONS: Impact of antibiotics on selecting ESBL-GNB at intestinal level varies if used in monotherapy or combination and according to previous antibiotic exposure. These finding should be explored in future clinical trials on antibiotic stewardship interventions. CLINICAL TRIAL REGISTRATION: NCT01208519.

Dynamics of the human gut phageome during antibiotic treatment.

Bacterial viruses contribute to the dynamics of the microbiome communities, as they are involved in the horizontal gene transfer. Previously we studied changes in the gut microbiome of the two healthy individuals over the course of a 6-days antibiotics treatment and subsequent 28 days recovery time (Willmann et al., 2015). Now, from the same samples, the virus-like particles were isolated and sequenced. As the phage sequences are currently poorly represented in reference databases, the reads had to be assembled, annotated and their abundance had to be evaluated via reads mapping. We analyzed and compared patterns of changes in abundance of the phage scaffolds and scaffolds with antibiotics resistant genes, in both phage and whole-genome metagenomic sets. We observed an increase in abundance of scaffolds carrying antibiotic-resistant genes in response to the treatment.

CLUSEAN: a computer-based framework for the automated analysis of bacterial secondary metabolite biosynthetic gene clusters.

Bacterial secondary metabolites are an important source of antimicrobial and cytostatic drugs. These molecules are often synthesized in a stepwise fashion by multimodular megaenzymes that are encoded in clusters of genes encoding enzymes for precursor supply and modification. In this work,we present an open source software pipeline, CLUSEAN (CLUster SEquence ANalyzer) that helps to annotate and analyze such gene clusters. CLUSEAN integrates standard analysis tools, like BLAST and HMMer, with specific tools for the identification of the functional domains and motifs in nonribosomal peptide synthetases (NRPS)/type I polyketide synthases (PKS) and the prediction of specificities of NRPS.

Phylogenetic super-networks from partial trees.

In practice, one is often faced with incomplete phylogenetic data, such as a collection of partial trees or partial splits. This paper poses the problem of inferring a phylogenetic super-network from such data and provides an efficient algorithm for doing so, called the Z-closure method. Additionally, the questions of assigning lengths to the edges of the network and how to restrict the "dimensionality" of the network are addressed. Applications to a set of five published partial gene trees relating different fungal species and to six published partial gene trees relating different grasses illustrate the usefulness of the method and an experimental study confirms its potential. The method is implemented as a plug-in for the program SplitsTree4.

Design of a compartmentalized shotgun assembler for the human genome.

Two different strategies for determining the human genome are currently being pursued: one is the "clone-by-clone" approach, employed by the publicly funded project, and the other is the "whole genome shotgun assembler" approach, favored by researchers at Celera Genomics. An interim strategy employed at Celera, called compartmentalized shotgun assembly, makes use of preliminary data produced by both approaches. In this paper we describe the design, implementation and operation of the "compartmentalized shotgun assembler".

The sequence of the human genome.

A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

The conserved exon method for gene finding.

A new approach to gene finding is introduced called the "Conserved Exon Method" (CEM). It is based on the idea of looking for conserved protein sequences by comparing pairs of DNA sequences, identifying putative exon pairs based on conserved regions and splice junction signals then chaining pairs of putative exons together. It simultaneously predicts gene structures in both human and mouse genomic sequences (or in other pairs of sequences at the appropriate evolutionary distance). Experimental results indicate the potential usefulness of this approach.

Disk-covering, a fast-converging method for phylogenetic tree reconstruction.

The evolutionary history of a set of species is represented by a phylogenetic tree, which is a rooted, leaf-labeled tree, where internal nodes represent ancestral species and the leaves represent modern day species. Accurate (or even boundedly inaccurate) topology reconstructions of large and divergent trees from realistic length sequences have long been considered one of the major challenges in systematic biology. In this paper, we present a simple method, the Disk-Covering Method (DCM), which boosts the performance of base phylogenetic methods under various Markov models of evolution. We analyze the performance of DCM-boosted distance methods under the Jukes-Cantor Markov model of biomolecular sequence evolution, and prove that for almost all trees, polylogarithmic length sequences suffice for complete accuracy with high probability, while polynomial length sequences always suffice. We also provide an experimental study based upon simulating sequence evolution on model trees. This study confirms substantial reductions in error rates at realistic sequence lengths.

Solving large scale phylogenetic problems using DCM2.

In an earlier paper, we described a new method for phylogenetic tree reconstruction called the Disk Covering Method, or DCM. This is a general method which can be used with any existing phylogenetic method in order to improve its performance. We showed analytically and experimentally that when DCM is used in conjunction with polynomial time distance-based methods, it improves the accuracy of the trees reconstructed. In this paper, we discuss a variant on DCM, that we call DCM2. DCM2 is designed to be used with phylogenetic methods whose objective is the solution of NP-hard optimization problems. We show that DCM2 can be used to accelerate searches for Maximum Parsimony trees. We also motivate the need for solutions to NP-hard optimization problems by showing that on some very large and important datasets, the most popular (and presumably best performing) polynomial time distance methods have poor accuracy.

A covariotide model explains apparent phylogenetic structure of oxygenic photosynthetic lineages.

The aims of the work were (1) to develop statistical tests to identify whether substitution takes place under a covariotide model in sequences used for phylogenetic inference and (2) to determine the influence of covariotide substitution on phylogenetic trees inferred for photosynthetic and other organisms. (Covariotide and covarion models are ones in which sites that are variable in some parts of the underlying tree are invariable in others and vice versa.) Two tests were developed. The first was a contingency test, and the second was an inequality test comparing the expected number of variable sites in two groups with the observed number. Application of these tests to 16S rDNA and tufA sequences from a range of nonphotosynthetic prokaryotes and oxygenic photosynthetic prokaryotes and eukaryotes suggests the occurrence of a covariotide mechanism. The degree of support for partitioning of taxa in reconstructed trees involving these organisms was determined in the presence or absence of sites showing particular substitution patterns. This analysis showed that the support for splits between (1) photosynthetic eukaryotes and prokaryotes and (2) photosynthetic and nonphotosynthetic organisms could be accounted for by patterns arising from covariotide substitution. We show that the additional problem of compositional bias in sequence data needs to be considered in the context of patterns of covariotide/covarion substitution. We argue that while covariotide or covarion substitution may give rise to phylogenetically informative patterns in sequence data, this may not always be so.

SplitsTree: analyzing and visualizing evolutionary data.

MOTIVATION: Real evolutionary data often contain a number of different and sometimes conflicting phylogenetic signals, and thus do not always clearly support a unique tree. To address this problem, Bandelt and Dress (Adv. Math., 92, 47-05, 1992) developed the method of split decomposition. For ideal data, this method gives rise to a tree, whereas less ideal data are represented by a tree-like network that may indicate evidence for different and conflicting phylogenies. RESULTS: SplitsTree is an interactive program, for analyzing and visualizing evolutionary data, that implements this approach. It also supports a number of distances transformations, the computation of parsimony splits, spectral analysis and bootstrapping.