SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification.

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.

Padhoc: a computational pipeline for pathway reconstruction on the fly.

MOTIVATION: Molecular pathway databases represent cellular processes in a structured and standardized way. These databases support the community-wide utilization of pathway information in biological research and the computational analysis of high-throughput biochemical data. Although pathway databases are critical in genomics research, the fast progress of biomedical sciences prevents databases from staying up-to-date. Moreover, the compartmentalization of cellular reactions into defined pathways reflects arbitrary choices that might not always be aligned with the needs of the researcher. Today, no tool exists that allow the easy creation of user-defined pathway representations. RESULTS: Here we present Padhoc, a pipeline for pathway ad hoc reconstruction. Based on a set of user-provided keywords, Padhoc combines natural language processing, database knowledge extraction, orthology search and powerful graph algorithms to create navigable pathways tailored to the user's needs. We validate Padhoc with a set of well-established Escherichia coli pathways and demonstrate usability to create not-yet-available pathways in model (human) and non-model (sweet orange) organisms. AVAILABILITY AND IMPLEMENTATION: Padhoc is freely available at https://github.com/ConesaLab/padhoc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Advances and Applications in the Quest for Orthologs.

Gene families evolve by the processes of speciation (creating orthologs), gene duplication (paralogs), and horizontal gene transfer (xenologs), in addition to sequence divergence and gene loss. Orthologs in particular play an essential role in comparative genomics and phylogenomic analyses. With the continued sequencing of organisms across the tree of life, the data are available to reconstruct the unique evolutionary histories of tens of thousands of gene families. Accurate reconstruction of these histories, however, is a challenging computational problem, and the focus of the Quest for Orthologs Consortium. We review the recent advances and outstanding challenges in this field, as revealed at a symposium and meeting held at the University of Southern California in 2017. Key advances have been made both at the level of orthology algorithm development and with respect to coordination across the community of algorithm developers and orthology end-users. Applications spanned a broad range, including gene function prediction, phylostratigraphy, genome evolution, and phylogenomics. The meetings highlighted the increasing use of meta-analyses integrating results from multiple different algorithms, and discussed ongoing challenges in orthology inference as well as the next steps toward improvement and integration of orthology resources.

Standardized benchmarking in the quest for orthologs.

Achieving high accuracy in orthology inference is essential for many comparative, evolutionary and functional genomic analyses, yet the true evolutionary history of genes is generally unknown and orthologs are used for very different applications across phyla, requiring different precision-recall trade-offs. As a result, it is difficult to assess the performance of orthology inference methods. Here, we present a community effort to establish standards and an automated web-based service to facilitate orthology benchmarking. Using this service, we characterize 15 well-established inference methods and resources on a battery of 20 different benchmarks. Standardized benchmarking provides a way for users to identify the most effective methods for the problem at hand, sets a minimum requirement for new tools and resources, and guides the development of more accurate orthology inference methods.

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text.

Motivation: Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. Results: We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. Availability and implementation: The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. Contact: andyli@ece.ufl.edu or aconesa@ufl.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Gearing up to handle the mosaic nature of life in the quest for orthologs.

The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches. Central to the QfO effort is proper benchmarking of methods and services, as well as design of standardized datasets and standardized formats to allow sharing and comparison of results. Simultaneously, analysis pipelines have been improved, evaluated and adapted to handle large datasets. All this would not have occurred without the long-term collaboration of Consortium members. Meeting regularly to review and coordinate complementary activities from a broad spectrum of innovative researchers clearly benefits the community. Highlights of the meeting include addressing sources of and legitimacy of disagreements between orthology calls, the context dependency of orthology definitions, special challenges encountered when analyzing very anciently rooted orthologies, orthology in the light of whole-genome duplications, and the concept of orthologous versus paralogous relationships at different levels, including domain-level orthology. Furthermore, particular needs for different applications (e.g. plant genomics, ancient gene families and others) and the infrastructure for making orthology inferences available (e.g. interfaces with model organism databases) were discussed, with several ongoing efforts that are expected to be reported on during the upcoming 2017 QfO meeting.

A meta-approach for improving the prediction and the functional annotation of ortholog groups.

BACKGROUND: In comparative genomics, orthologs are used to transfer annotation from genes already characterized to newly sequenced genomes. Many methods have been developed for finding orthologs in sets of genomes. However, the application of different methods on the same proteome set can lead to distinct orthology predictions. METHODS: We developed a method based on a meta-approach that is able to combine the results of several methods for orthologous group prediction. The purpose of this method is to produce better quality results by using the overlapping results obtained from several individual orthologous gene prediction procedures. Our method proceeds in two steps. The first aims to construct seeds for groups of orthologous genes; these seeds correspond to the exact overlaps between the results of all or several methods. In the second step, these seed groups are expanded by using HMM profiles. RESULTS: We evaluated our method on two standard reference benchmarks, OrthoBench and Orthology Benchmark Service. Our method presents a higher level of accurately predicted groups than the individual input methods of orthologous group prediction. Moreover, our method increases the number of annotated orthologous pairs without decreasing the annotation quality compared to twelve state-of-the-art methods. CONCLUSIONS: The meta-approach based method appears to be a reliable procedure for predicting orthologous groups. Since a large number of methods for predicting groups of orthologous genes exist, it is quite conceivable to apply this meta-approach to several combinations of different methods.

MEPO-ML: a robust graph attention network model for rapid generation of partial atomic charges in metal-organic frameworks.

Accurate computation of the gas adsorption properties of MOFs is usually bottlenecked by the DFT calculations required to generate partial atomic charges. Therefore, large virtual screenings of MOFs often use the QEq method which is rapid, but of limited accuracy. Recently, machine learning (ML) models have been trained to generate charges in much better agreement with DFT-derived charges compared to the QEq models. Previous ML charge models for MOFs have all used training sets with less than 3000 MOFs obtained from the CoRE MOF database, which has recently been shown to have high structural error rates. In this work, we developed a graph attention network model for predicting DFT-derived charges in MOFs where the model was developed with the ARC-MOF database that contains 279,632 MOFs and over 40 million charges. This model, which we call MEPO-ML, predicts charges with a mean absolute error of 0.025e on our test set of over 27 K MOFs. Other ML models reported in the literature were also trained using the same dataset and descriptors, and MEPO-ML was shown to give the lowest errors. The gas adsorption properties evaluated using MEPO-ML charges are found to be in significantly better agreement with the reference DFT-derived charges compared to the empirical charges, for both polar and non-polar gases. Using only a single CPU core on our benchmark computer, MEPO-ML charges can be generated in less than two seconds on average (including all computations required to apply the model) for MOFs in the test set of 27 K MOFs.

The absence of the queuosine tRNA modification leads to pleiotropic phenotypes revealing perturbations of metal and oxidative stress homeostasis in Escherichia coli K12.

Queuosine (Q) is a conserved hypermodification of the wobble base of tRNA containing GUN anticodons but the physiological consequences of Q deficiency are poorly understood in bacteria. This work combines transcriptomic, proteomic and physiological studies to characterize a Q-deficient Escherichia coli K12 MG1655 mutant. The absence of Q led to an increased resistance to nickel and cobalt, and to an increased sensitivity to cadmium, compared to the wild-type (WT) strain. Transcriptomic analysis of the WT and Q-deficient strains, grown in the presence and absence of nickel, revealed that the nickel transporter genes (nikABCDE) are downregulated in the Q- mutant, even when nickel is not added. This mutant is therefore primed to resist to high nickel levels. Downstream analysis of the transcriptomic data suggested that the absence of Q triggers an atypical oxidative stress response, confirmed by the detection of slightly elevated reactive oxygen species (ROS) levels in the mutant, increased sensitivity to hydrogen peroxide and paraquat, and a subtle growth phenotype in a strain prone to accumulation of ROS.

Assessment of unconventional antimicrobial compounds for the control of 'Candidatus Liberibacter asiaticus', the causative agent of citrus greening disease.

In this study, newly identified small molecules were examined for efficacy against 'Candidatus Liberibacter asiaticus' in commercial groves of sweet orange (Citrus sinensis) and white grapefruit (Citrus paradisi) trees. We used benzbromarone and/or tolfenamic acid delivered by trunk injection. We evaluated safety and efficacy parameters by performing RNAseq of the citrus host responses, 16S rRNA gene sequencing to characterize citrus-associated microbial communities during treatment, and qRT-PCR as an indirect determination of 'Ca. L. asiaticus' viability. Analyses of the C. sinensis transcriptome indicated that each treatment consistently induced genes associated with normal metabolism and growth, without compromising tree viability or negatively affecting the indigenous citrus-associated microbiota. It was found that treatment-associated reduction in 'Ca. L. asiaticus' was positively correlated with the proliferation of several core taxa related with citrus health. No symptoms of phytotoxicity were observed in any of the treated trees. Trials were also performed in commercial groves to examine the effect of each treatment on fruit productivity, juice quality and efficacy against 'Ca. L. asiaticus'. Increased fruit production (15%) was observed in C. paradisi following twelve months of treatment with benzbromarone and tolfenamic acid. These results were positively correlated with decreased 'Ca. L. asiaticus' transcriptional activity in root samples.

Comparative Metagenomics Provides Insight Into the Ecosystem Functioning of the Shark Bay Stromatolites, Western Australia.

Stromatolites are organosedimentary build-ups that have formed as a result of the sediment trapping, binding and precipitating activities of microbes. Today, extant systems provide an ideal platform for understanding the structure, composition, and interactions between stromatolite-forming microbial communities and their respective environments. In this study, we compared the metagenomes of three prevalent stromatolite-forming microbial mat types in the Spaven Province of Hamelin Pool, Shark Bay located in Western Australia. These stromatolite-forming mat types included an intertidal pustular mat as well as a smooth and colloform mat types located in the subtidal zone. Additionally, the metagenomes of an adjacent, non-lithifying mat located in the upper intertidal zone were also sequenced for comparative purposes. Taxonomic and functional gene analyses revealed distinctive differences between the lithifying and non-lithifying mat types, which strongly correlated with water depth. Three distinct populations emerged including the upper intertidal non-lithifying mats, the intertidal pustular mats associated with unlaminated carbonate build-ups, and the subtidal colloform and smooth mat types associated with laminated structures. Functional analysis of metagenomes revealed that amongst stromatolite-forming mats there was an enrichment of photosynthesis pathways in the pustular stromatolite-forming mats. In the colloform and smooth stromatolite-forming mats, however, there was an increase in the abundance of genes associated with those heterotrophic metabolisms typically associated with carbonate mineralization, such as sulfate reduction. The comparative metagenomic analyses suggest that stromatolites of Hamelin Pool may form by two distinctive processes that are highly dependent on water depth. These results provide key insight into the potential adaptive strategies and synergistic interactions between microbes and their environments that may lead to stromatolite formation and accretion.

Effects of inhaled fenoterol and positive end-expiratory pressure on the respiratory mechanics of patients with chronic obstructive pulmonary disease.

BACKGROUND: During acute ventilatory failure in patients with chronic obstructive pulmonary disease (COPD), applying external positive end-expiratory pressure (PEEPe) will reopen small airways and, thus, may enhance peripheral deposition as well as the physiological effects of inhaled beta-2 agonists. OBJECTIVE: To investigate the efficacy of inhaled fenoterol applied by zero end-expiratory pressure (ZEEPe) or PEEPe. METHODS: Ten patients with COPD who were intubated and mechanically ventilated received fenoterol (10 mg/4 mL) via the ventilator using a jet nebulizer for 30 min on ZEEPe and PEEPe set at 80% of the total PEEP in a random order. The total resistance of the respiratory system (rapid airway occlusion technique), change in end-expiratory lung volume and expiratory flow limitation were assessed before and 5 min, 15 min, 30 min, 60 min and 240 min after fenoterol inhalation. RESULTS: Before inhalation and 60 min after inhalation, the total PEEP, the change in end-expiratory lung volume and the total resistance of the respiratory system were 8+/-3 cmH2O and 6+/-3 cmH2O, 0.61+/-0.34 L and 0.43+/-0.32 L, and 26+/-7 cmH2O/L/s and 23+/-6 cmH2O/L/s, respectively, with ZEEPe, and 9+/-3 cmH2O and 8+/-3 cmH2O (P<0.05 versus ZEEPe), 0.62+/-0.34 L and 0.62+/-0.37 L (P<0.05 versus ZEEPe), and 26+/-9 H2O/L/s and 25+/-9 H2O/L/s, respectively, with PEEPe. Three patients became not flow-limited under the combination of PEEPe and fenoterol. CONCLUSIONS: In patients with COPD, fenoterol combined with PEEPe has opposing effects on respiratory mechanics. First, it does not significantly reduce lung hyperinflation or inspiratory resistances. Second, it allows expiratory flow limitation reversal in some patients. These findings result from the net effect on end-expiratory lung volume of each intervention. This implies that if fenoterol is used in combination with PEEPe, the level of PEEPe should be reassessed during the time course of the drug to prevent any further lung hyperinflation.

Fatal varicella hepatitis in an asthmatic adult after short-term corticosteroid treatment.

A 28-year-old male patient, treated with prednisone for bronchitis with sibilant rales, developed fever with abdominal pain and generalized vesicular rash after coming in contact with varicella-infected children. He was hospitalized after having a seizure. Laboratory values revealed hepatitis and rapidly fulminant hepatic insufficiency with disseminated intravascular coagulation. Despite acyclovir treatment, the patient died 4 days after admission. Clinical presentation could evoke a Reye's syndrome, but liver biopsy showed massive coagulative necrosis. This report demonstrates the increased risk of complicated varicella associated with the use of corticosteroids, even for a short period of time.

Sigmoidal equation for lung and chest wall volume-pressure curves in acute respiratory failure.

To assess incidence and magnitude of the "lower inflection point" of the chest wall, the sigmoidal equation was used in 36 consecutive patients intubated and mechanically ventilated with acute lung injury (ALI). They were 21 primary and 5 secondary ALI, 6 unilateral pneumonia, and 4 cardiogenic pulmonary edema. The lower inflection point was estimated as the point of maximal compliance increase. The low constant flow inflation method and esophageal pressure were used to partition the volume-pressure curves into their chest wall and lung components on zero end-expiratory pressure. The sigmoidal equation had an excellent fit with coefficients of determination >0.90 in all instances. The point of maximal compliance increase of the chest wall ranged from 0 to 8.3 cmH2O (median 1 cmH2O) with no difference between ALI groups. The chest wall significantly contributed to the lower inflection point of the respiratory system in eight patients only. The occurrence of a significant contribution of the chest wall to the lower inflection point of the respiratory system is lower than anticipated. The sigmoidal equation is able to determine precisely the point of the maximal compliance increase of lung and chest wall.

Long-term mechanical ventilation equipment for neuromuscular patients: meeting the expectations of patients and prescribers.

BACKGROUND: To maximize the likelihood of successful long-term mechanical ventilation (MV) in patients with neuromuscular diseases, ventilator characteristics and settings must be chosen carefully, taking into account both medical requisites and the patient's preference and comfort. OBJECTIVES: To evaluate patients' knowledge about and comfort with their long-term MV; to compare patients' and prescribers' opinions and expectations regarding long-term MV; and to compare the equipment used by the patients to the prescribers' current MV prescription. METHODS: Neuromuscular patients receiving long-term MV, and home MV prescribers in Belgium and France were asked to respond to a questionnaire survey specifically developed for the study. RESULTS: Completed questionnaires were collected from 209 patients (mean age 35.4 ± 15.9 y, range 3-86 y), ventilated since 11 ± 17 year, and 45 MV prescribers. One hundred sixty-three (78%) patients correctly designated their MV mode as a volume or pressure controlled mode. When an inspiratory trigger was available, 92% of the patients were able to use it, but only 69% were satisfied. Prescribers were more prone than patients to use new technologies such as an emergency-release system for the noninvasive interface (1-10 visual analog scale score 9.2 ± 1.5 vs 6.8 ± 3.3, P < .001), a humidification system (8.6 ± 1.4 vs 7.8 ± 2.6, P = .02), a contactor for providing larger inspiratory volumes (8.4 ± 1.7 vs 6.0 ± 3.0, P = .009), a built-in cough assistance mode (9.2 ± 1.4 vs 5.5 ± 3.5, P < .001), new options to improve speech, or new MV modes such as a volume-targeted pressure control. CONCLUSIONS: The opinions of patients and prescribers differed about the ideal home ventilator. Patients were less prone to use new technologies, mainly because of a lack of information, underlining the need for regular MV update in patients receiving long-term MV.