Viroscope: Plant viral diagnosis from high-throughput sequencing data using biologically-informed genome assembly coverage.

High-throughput sequencing (HTS) methods are transforming our capacity to detect pathogens and perform disease diagnosis. Although sequencing advances have enabled accessible and point-of-care HTS, data analysis pipelines have yet to provide robust tools for precise and certain diagnosis, particularly in cases of low sequencing coverage. Lack of standardized metrics and harmonized detection thresholds confound the problem further, impeding the adoption and implementation of these solutions in real-world applications. In this work, we tackle these issues and propose biologically-informed viral genome assembly coverage as a method to improve diagnostic certainty. We use the identification of viral replicases, an essential function of viral life cycles, to define genome coverage thresholds in which biological functions can be described. We validate the analysis pipeline, Viroscope, using field samples, synthetic and published datasets, and demonstrate that it provides sensitive and specific viral detection. Furthermore, we developed Viroscope.io a web-service to provide on-demand HTS data viral diagnosis to facilitate adoption and implementation by phytosanitary agencies to enable precise viral diagnosis.

Evaluation of computational methods for human microbiome analysis using simulated data.

BACKGROUND: Our understanding of the composition, function, and health implications of human microbiota has been advanced by high-throughput sequencing and the development of new genomic analyses. However, trade-offs among alternative strategies for the acquisition and analysis of sequence data remain understudied. METHODS: We assessed eight popular taxonomic profiling pipelines; MetaPhlAn2, metaMix, PathoScope 2.0, Sigma, Kraken, ConStrains, Centrifuge and Taxator-tk, against a battery of metagenomic datasets simulated from real data. The metagenomic datasets were modeled on 426 complete or permanent draft genomes stored in the Human Oral Microbiome Database and were designed to simulate various experimental conditions, both in the design of a putative experiment; read length (75-1,000 bp reads), sequence depth (100K-10M), and in metagenomic composition; number of species present (10, 100, 426), species distribution. The sensitivity and specificity of each of the pipelines under various scenarios were measured. We also estimated the relative root mean square error and average relative error to assess the abundance estimates produced by different methods. Additional datasets were generated for five of the pipelines to simulate the presence within a metagenome of an unreferenced species, closely related to other referenced species. Additional datasets were also generated in order to measure computational time on datasets of ever-increasing sequencing depth (up to 6 × 107). RESULTS: Testing of eight pipelines against 144 simulated metagenomic datasets initially produced 1,104 discrete results. Pipelines using a marker gene strategy; MetaPhlAn2 and ConStrains, were overall less sensitive, than other pipelines; with the notable exception of Taxator-tk. This difference in sensitivity was largely made up in terms of runtime, significantly lower than more sensitive pipelines that rely on whole-genome alignments such as PathoScope2.0. However, pipelines that used strategies to speed-up alignment between genomic references and metagenomic reads, such as kmerization, were able to combine both high sensitivity and low run time, as is the case with Kraken and Centrifuge. Absent species genomes in the database mostly led to assignment of reads to the most closely related species available in all pipelines. Our results therefore suggest that taxonomic profilers that use kmerization have largely superseded those that use gene markers, coupling low run times with high sensitivity and specificity. Taxonomic profilers using more time-consuming read reassignment, such as PathoScope 2.0, provided the most sensitive profiles under common metagenomic sequencing scenarios. All the results described and discussed in this paper can be visualized using the dedicated R Shiny application (https://github.com/microgenomics/HumanMicrobiomeAnalysis). All of our datasets, pipelines and results are made available through the GitHub repository for future benchmarking.

Genome sequence of two members of the chloroaromatic-degrading MT community: Pseudomonas reinekei MT1 and Achromobacter xylosoxidans MT3.

We describe the genome sequence of Pseudomonas reinekei MT1 and Achromobacter xylosoxidans MT3, the most abundant members of a bacterial community capable of degrading chloroaromatic compounds. The MT1 genome contains open reading frames encoding enzymes responsible for the catabolism of chlorosalicylate, methylsalicylate, chlorophenols, phenol, benzoate, p-coumarate, phenylalanine, and phenylacetate. On the other hand, the MT3 strain genome possesses no ORFs to metabolize chlorosalicylates; instead the bacterium is capable of metabolizing nitro-phenolic and phenolic compounds, which can be used as the only carbon and energy source by MT3. We also confirmed that MT3 displays the genetic machinery for the metabolism of chlorocathecols and chloromuconates, where the latter are toxic compounds secreted by MT1 when degrading chlorosalicylates. Altogether, this work will advance our fundamental understanding of bacterial interactions.

Computational Methods for Human Microbiome Analysis.

As the field of microbiomics advances, the burden of computational work that scientists need to perform in order to extract biological insight has grown accordingly. Likewise, while human microbiome analyses are increasingly shifting toward a greater integration of various high-throughput data types, a core number of methods form the basis of nearly every study. In this unit, we present step-by-step protocols for five core stages of human microbiome research. The protocols presented in this unit provide a base case for human microbiome analysis, complete with sufficient detail for researchers to tailor certain aspects of the protocols to the specificities of their data. © 2017 by John Wiley & Sons, Inc.

Draft Genome Sequences of Five Enterococcus Species Isolated from the Gut of Patients with Suspected Clostridium difficile Infection.

We present draft genome sequences of five Enterococcus species from patients suspected of Clostridium difficile infection. Genome completeness was confirmed by presence of bacterial orthologs (97%). Gene searches using Hidden-Markov models revealed that the isolates harbor between seven and 11 genes involved in antibiotic resistance to tetracyclines, beta-lactams, and vancomycin.

Comparative Genomics Analysis of a New Exiguobacterium Strain from Salar de Huasco Reveals a Repertoire of Stress-Related Genes and Arsenic Resistance.

The Atacama Desert hosts diverse ecosystems including salt flats and shallow Andean lakes. Several heavy metals are found in the Atacama Desert, and microorganisms growing in this environment show varying levels of resistance/tolerance to copper, tellurium, and arsenic, among others. Herein, we report the genome sequence and comparative genomic analysis of a new Exiguobacterium strain, sp. SH31, isolated from an altiplanic shallow athalassohaline lake. Exiguobacterium sp. SH31 belongs to the phylogenetic Group II and its closest relative is Exiguobacterium sp. S17, isolated from the Argentinian Altiplano (95% average nucleotide identity). Strain SH31 encodes a wide repertoire of proteins required for cadmium, copper, mercury, tellurium, chromium, and arsenic resistance. Of the 34 Exiguobacterium genomes that were inspected, only isolates SH31 and S17 encode the arsenic efflux pump Acr3. Strain SH31 was able to grow in up to 10 mM arsenite and 100 mM arsenate, indicating that it is arsenic resistant. Further, expression of the ars operon and acr3 was strongly induced in response to both toxics, suggesting that the arsenic efflux pump Acr3 mediates arsenic resistance in Exiguobacterium sp. SH31.

Genome Sequence of Clostridium paraputrificum 373-A1 Isolated in Chile from a Patient Infected with Clostridium difficile.

Clostridium paraputrificum is a gut microbiota member reported in several cases of bacteremia and coinfections. So far, only one genome sequence of a C. paraputrificum (AGR2156) isolate is available. Here, we present the draft genome of C. paraputrificum strain 373-A1, isolated from stools from a patient with C. difficile infection.

Interdomain Contacts Control Native State Switching of RfaH on a Dual-Funneled Landscape.

RfaH is a virulence factor from Escherichia coli whose C-terminal domain (CTD) undergoes a dramatic α-to-ß conformational transformation. The CTD in its α-helical fold is stabilized by interactions with the N-terminal domain (NTD), masking an RNA polymerase binding site until a specific recruitment site is encountered. Domain dissociation is triggered upon binding to DNA, allowing the NTD to interact with RNA polymerase to facilitate transcription while the CTD refolds into the ß-barrel conformation that interacts with the ribosome to activate translation. However, structural details of this transformation process in the context of the full protein remain to be elucidated. Here, we explore the mechanism of the α-to-ß conformational transition of RfaH in the full-length protein using a dual-basin structure-based model. Our simulations capture several features described experimentally, such as the requirement of disruption of interdomain contacts to trigger the α-to-ß transformation, confirms the roles of previously indicated residues E48 and R138, and suggests a new important role for F130, in the stability of the interdomain interaction. These native basins are connected through an intermediate state that builds up upon binding to the NTD and shares features from both folds, in agreement with previous in silico studies of the isolated CTD. We also examine the effect of RNA polymerase binding on the stabilization of the ß fold. Our study shows that native-biased models are appropriate for interrogating the detailed mechanisms of structural rearrangements during the dramatic transformation process of RfaH.