Bendamustine, bortezomib and rituximab produces durable complete remissions in patients with previously untreated, low grade lymphoma.

This Phase II trial evaluated the efficacy of bendamustine, bortezomib and rituximab in patients with previously untreated low-grade lymphoma. Eligible patients had low grade lymphoma with no previous systemic disease treatment. Treatment for all patients was given in 28-day cycles for a maximum of 6 cycles. Patients received rituximab 375 mg/m2 intravenously (IV) on days 1, 8 and 15 of cycle 1 and day 1 of cycles 2-6; bendamustine 90 mg/m2 IV on days 1 and 2; and bortezomib 1·6 mg/m2 IV on days 1, 8 and 15. Patients were permitted to begin maintenance treatment with rituximab 6 months after completion of study treatment and after 6-month follow-up assessments had been conducted. Fifty-four eligible patients were enrolled. The most common grade 3/4 toxicities were leucopenia (28%), neutropenia (30%) and lymphopenia (17%). There were no treatment-related deaths and 1 unrelated death on study (embolic stroke). The overall response rate was 94% for all patients. The median follow-up was 54 months. Kaplan-Meier estimates of progression-free survival and overall survival at 36 months were 75% and 88%, respectively. The treatment regimen was well tolerated and produced high response rates. Further study of this regimen in patients with previously untreated lymphoma is warranted.

PMAnalyzer: a new web interface for bacterial growth curve analysis.

SUMMARY: Bacterial growth curves are essential representations for characterizing bacteria metabolism within a variety of media compositions. Using high-throughput, spectrophotometers capable of processing tens of 96-well plates, quantitative phenotypic information can be easily integrated into the current data structures that describe a bacterial organism. The PMAnalyzer pipeline performs a growth curve analysis to parameterize the unique features occurring within microtiter wells containing specific growth media sources. We have expanded the pipeline capabilities and provide a user-friendly, online implementation of this automated pipeline. PMAnalyzer version 2.0 provides fast automatic growth curve parameter analysis, growth identification and high resolution figures of sample-replicate growth curves and several statistical analyses. AVAILABILITY AND IMPLEMENTATION: PMAnalyzer v2.0 can be found at https://edwards.sdsu.edu/pmanalyzer/ . Source code for the pipeline can be found on GitHub at https://github.com/dacuevas/PMAnalyzer . Source code for the online implementation can be found on GitHub at https://github.com/dacuevas/PMAnalyzerWeb . CONTACT: dcuevas08@gmail.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Comparative genomics of 274 Vibrio cholerae genomes reveals mobile functions structuring three niche dimensions.

BACKGROUND: Vibrio cholerae is a globally dispersed pathogen that has evolved with humans for centuries, but also includes non-pathogenic environmental strains. Here, we identify the genomic variability underlying this remarkable persistence across the three major niche dimensions space, time, and habitat. RESULTS: Taking an innovative approach of genome-wide association applicable to microbial genomes (GWAS-M), we classify 274 complete V. cholerae genomes by niche, including 39 newly sequenced for this study with the Ion Torrent DNA-sequencing platform. Niche metadata were collected for each strain and analyzed together with comprehensive annotations of genetic and genomic attributes, including point mutations (single-nucleotide polymorphisms, SNPs), protein families, functions and prophages. CONCLUSIONS: Our analysis revealed that genomic variations, in particular mobile functions including phages, prophages, transposable elements, and plasmids underlie the metadata structuring in each of the three niche dimensions. This underscores the role of phages and mobile elements as the most rapidly evolving elements in bacterial genomes, creating local endemicity (space), leading to temporal divergence (time), and allowing the invasion of new habitats. Together, we take a data-driven approach for comparative functional genomics that exploits high-volume genome sequencing and annotation, in conjunction with novel statistical and machine learning analyses to identify connections between genotype and phenotype on a genome-wide scale.

Accessing the SEED genome databases via Web services API: tools for programmers.

BACKGROUND: The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. RESULTS: The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. CONCLUSIONS: We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

Towards Predicting Gut Microbial Metabolism: Integration of Flux Balance Analysis and Untargeted Metabolomics.

Genomics-based metabolic models of microorganisms currently have no easy way of corroborating predicted biomass with the actual metabolites being produced. This study uses untargeted mass spectrometry-based metabolomics data to generate a list of accurate metabolite masses produced from the human commensal bacteria Citrobacter sedlakii grown in the presence of a simple glucose carbon source. A genomics-based flux balance metabolic model of this bacterium was previously generated using the bioinformatics tool PyFBA and phenotypic growth curve data. The high-resolution mass spectrometry data obtained through timed metabolic extractions were integrated with the predicted metabolic model through a program called MS_FBA. This program correlated untargeted metabolomics features from C. sedlakii with 218 of the 699 metabolites in the model using an exact mass match, with 51 metabolites further confirmed using predicted isotope ratios. Over 1400 metabolites were matched with additional metabolites in the ModelSEED database, indicating the need to incorporate more specific gene annotations into the predictive model through metabolomics-guided gap filling.

Dietary prophage inducers and antimicrobials: toward landscaping the human gut microbiome.

The approximately 1011 viruses and microbial cells per gram of fecal matter (dry weight) in the large intestine are important to human health. The responses of three common gut bacteria species, and one opportunistic pathogen, to 117 commonly consumed foods, chemical additives, and plant extracts were tested. Many compounds, including Stevia rebaudiana and bee propolis extracts, exhibited species-specific growth inhibition by prophage induction. Overall, these results show that various foods may change the abundances of gut bacteria by modulating temperate phage and suggests a novel path for landscaping the human gut microbiome.

Cystic Fibrosis Rapid Response: Translating Multi-omics Data into Clinically Relevant Information.

Pulmonary exacerbations are the leading cause of death in cystic fibrosis (CF) patients. To track microbial dynamics during acute exacerbations, a CF rapid response (CFRR) strategy was developed. The CFRR relies on viromics, metagenomics, metatranscriptomics, and metabolomics data to rapidly monitor active members of the viral and microbial community during acute CF exacerbations. To highlight CFRR, a case study of a CF patient is presented, in which an abrupt decline in lung function characterized a fatal exacerbation. The microbial community in the patient's lungs was closely monitored through the multi-omics strategy, which led to the identification of pathogenic shigatoxigenic Escherichia coli (STEC) expressing Shiga toxin. This case study illustrates the potential for the CFRR to deconstruct complicated disease dynamics and provide clinicians with alternative treatments to improve the outcomes of pulmonary exacerbations and expand the life spans of individuals with CF.IMPORTANCE Proper management of polymicrobial infections in patients with cystic fibrosis (CF) has extended their life span. Information about the composition and dynamics of each patient's microbial community aids in the selection of appropriate treatment of pulmonary exacerbations. We propose the cystic fibrosis rapid response (CFRR) as a fast approach to determine viral and microbial community composition and activity during CF pulmonary exacerbations. The CFRR potential is illustrated with a case study in which a cystic fibrosis fatal exacerbation was characterized by the presence of shigatoxigenic Escherichia coli The incorporation of the CFRR within the CF clinic could increase the life span and quality of life of CF patients.

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage.

Microbiomes are vast communities of microorganisms and viruses that populate all natural ecosystems. Viruses have been considered to be the most variable component of microbiomes, as supported by virome surveys and examples of high genomic mosaicism. However, recent evidence suggests that the human gut virome is remarkably stable compared with that of other environments. Here, we investigate the origin, evolution and epidemiology of crAssphage, a widespread human gut virus. Through a global collaboration, we obtained DNA sequences of crAssphage from more than one-third of the world's countries and showed that the phylogeography of crAssphage is locally clustered within countries, cities and individuals. We also found fully colinear crAssphage-like genomes in both Old-World and New-World primates, suggesting that the association of crAssphage with primates may be millions of years old. Finally, by exploiting a large cohort of more than 1,000 individuals, we tested whether crAssphage is associated with bacterial taxonomic groups of the gut microbiome, diverse human health parameters and a wide range of dietary factors. We identified strong correlations with different clades of bacteria that are related to Bacteroidetes and weak associations with several diet categories, but no significant association with health or disease. We conclude that crAssphage is a benign cosmopolitan virus that may have coevolved with the human lineage and is an integral part of the normal human gut virome.

Growth Score: a single metric to define growth in 96-well phenotype assays.

High-throughput phenotype assays are a cornerstone of systems biology as they allow direct measurements of mutations, genes, strains, or even different genera. High-throughput methods also require data analytic methods that reduce complex time-series data to a single numeric evaluation. Here, we present the Growth Score, an improvement on the previous Growth Level formula. There is strong correlation between Growth Score and Growth Level, but the new Growth Score contains only essential growth curve properties while the formula of the previous Growth Level was convoluted and not easily interpretable. Several programs can be used to estimate the parameters required to calculate the Growth Score metric, including our PMAnalyzer pipeline.

From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model.

Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe's entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Python-based open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe's metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models.

Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins.

Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.

FOCUS: an alignment-free model to identify organisms in metagenomes using non-negative least squares.

One of the major goals in metagenomics is to identify the organisms present in a microbial community from unannotated shotgun sequencing reads. Taxonomic profiling has valuable applications in biological and medical research, including disease diagnostics. Most currently available approaches do not scale well with increasing data volumes, which is important because both the number and lengths of the reads provided by sequencing platforms keep increasing. Here we introduce FOCUS, an agile composition based approach using non-negative least squares (NNLS) to report the organisms present in metagenomic samples and profile their abundances. FOCUS was tested with simulated and real metagenomes, and the results show that our approach accurately predicts the organisms present in microbial communities. FOCUS was implemented in Python. The source code and web-sever are freely available at http://edwards.sdsu.edu/FOCUS.

Sequencing at sea: challenges and experiences in Ion Torrent PGM sequencing during the 2013 Southern Line Islands Research Expedition.

Genomics and metagenomics have revolutionized our understanding of marine microbial ecology and the importance of microbes in global geochemical cycles. However, the process of DNA sequencing has always been an abstract extension of the research expedition, completed once the samples were returned to the laboratory. During the 2013 Southern Line Islands Research Expedition, we started the first effort to bring next generation sequencing to some of the most remote locations on our planet. We successfully sequenced twenty six marine microbial genomes, and two marine microbial metagenomes using the Ion Torrent PGM platform on the Merchant Yacht Hanse Explorer. Onboard sequence assembly, annotation, and analysis enabled us to investigate the role of the microbes in the coral reef ecology of these islands and atolls. This analysis identified phosphonate as an important phosphorous source for microbes growing in the Line Islands and reinforced the importance of L-serine in marine microbial ecosystems. Sequencing in the field allowed us to propose hypotheses and conduct experiments and further sampling based on the sequences generated. By eliminating the delay between sampling and sequencing, we enhanced the productivity of the research expedition. By overcoming the hurdles associated with sequencing on a boat in the middle of the Pacific Ocean we proved the flexibility of the sequencing, annotation, and analysis pipelines.

Proceso enfermero en un paciente pediátrico con falla cardiopulmonar sometido a oxigenación por membrana extracorpórea / Nursing process in a pediatric patient with cardiopulmonary failure undergoing extracorporeal membrane oxygenation

Background: Extracorporeal membrane oxygenation (ECMO) is an alternative treatment for patients with ventricular failure Postcardiotomy for surgical correction of Tetralogy of Fallot (TF); however, little evidence exists in Mexico for use in health institutions. Objective: To develop the process of nursing care (PAE) in infants patient with right lung failure and underwent ECMO. Methodology: Case study, prospective, longitudinal performed with the methodology of PAE in an institution of cardiovascular highly specialized in the mediate and immediate postoperative period. Altered human needs with cardiovascular assessment tool based nursing approach Henderson and expressly management tool for ECMO with hemodynamic and ventilatory variables were detected; nursing diagnoses (DE) real and assessed risk scoring DIANA, the higher the score greater independence were made; NIC interventions were raised. Data analyzed with descriptive statistics and paired t-test, significance p < 0.05. Results: Altered Needs: aeration/circulation, thermoregulation, avoid hazards; nursing diagnosis: impaired gas exchange, decreased cardiac output, temperature imbalance, risk of infection, bleeding risk. Tas NIC interventions and management of ECMO DIANA score increased, increasing the GC, acid-base balance was maintained, improved gas exchange with low ventilatory parameters; reduced the need for vasopressors and only required pharmacological support (levosimendan) 48 hours after starting ECMO. By increasing the basal parameters ECMO day to day one, there are significant hemodynamic and ventilatory changes (p < 0.05). On the 12th day ECMO is removed A successfully extubated. Conclusion: The perfusionist nurse through the implementation of SAP and ECMO, managed to provide quality care to pediatric patient safety and managing to satisfy the altered needs and solve the DE.

Introducción: La oxigenación por membrana extracorpórea (ECMO) es una alternativa de tratamiento para los pacientes con falla ventricular poscardiotomía por corrección quirúrgica de la tetralogía de Fallot; no obstante, existe poca evidencia en México de su uso en las instituciones de salud. Objetivo: desarrollar el proceso de atención de enfermería (PAE) en un lactante menor con falla derecha y pulmonar sometido a ECMO. Metodología: Estudio de caso, prospectivo y longitudinal realizado con la metodología del PAE en una Institución de Alta Especialidad Cardiovascular en el posoperatorio mediato e inmediato. Se detectaron necesidades humanas alteradas con el instrumento de valoración de enfermería cardiovascular basado en el enfoque de Henderson y un instrumento ex-profeso para el manejo del ECMO con las variables hemodinámicas y ventilatorias; se formularon diagnósticos reales de enfermería y de riesgo evaluados con puntuación DIANA, a mayor puntuación mayor independencia; se plantearon intervenciones NIC. Datos analizados con estadística descriptiva y prueba T pareada, significancia p < 0.05. Resultados: Necesidades alteradas: oxigenación/circulación, termorregulación y evitar peligros. Diagnósticos de enfermería: deterioro del intercambio gaseoso, disminución del gasto cardiaco, desequilibrio de la temperatura, riesgo de infección, riesgo de sangrado. Tras las intervenciones de NIC y el manejo de la ECMO se incrementó la puntuación DIANA y el gasto cardiaco; se mantuvo equilibrio ácido-base, mejoró el intercambio gaseoso con parámetros ventilatorios bajos; se redujo la necesidad de vasopresores y sólo requirió soporte farmacológico (levosimendán) 48 horas después de iniciada la ECMO. Al incrementar parámetros del ECMO del día basal a los subsecuentes, hay cambios hemodinámicos y/o ventilatorios significativos (p < 0.05). El día 12 del posoperatorio se retiró el ECMO, siete días después se extubó exitosamente y 10 días posteriores egresó a domicilio. Conclusión: Se logró satisfacer las necesidades alteradas del lactante a través del ECMO, con base en la aplicación del PAE.