Deep learning methods for drug response prediction in cancer: Predominant and emerging trends.

Cancer claims millions of lives yearly worldwide. While many therapies have been made available in recent years, by in large cancer remains unsolved. Exploiting computational predictive models to study and treat cancer holds great promise in improving drug development and personalized design of treatment plans, ultimately suppressing tumors, alleviating suffering, and prolonging lives of patients. A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods. These papers investigate diverse data representations, neural network architectures, learning methodologies, and evaluations schemes. However, deciphering promising predominant and emerging trends is difficult due to the variety of explored methods and lack of standardized framework for comparing drug response prediction models. To obtain a comprehensive landscape of deep learning methods, we conducted an extensive search and analysis of deep learning models that predict the response to single drug treatments. A total of 61 deep learning-based models have been curated, and summary plots were generated. Based on the analysis, observable patterns and prevalence of methods have been revealed. This review allows to better understand the current state of the field and identify major challenges and promising solution paths.

Genomic Analysis of Metastatic Solid Tumors in Veterans: Findings From the VHA National Precision Oncology Program.

PURPOSE: The Veterans Health Administration (VHA) is the largest cancer care provider in the United States, with the added challenge of serving more than twice the percentage of patients with cancer in rural areas than the national average. The VHA established the National Precision Oncology Program in 2016 to implement and standardize the practice of precision oncology across the diverse VHA system. METHODS: Tumor or peripheral blood specimens from veterans with advanced solid tumors who were eligible for treatment were submitted for next-generation sequencing (NGS) at two commercial laboratories. Annotated results were generated by the laboratories and independently using IBM Watson for Genomics. Levels-of-evidence treatment recommendations were based on OncoKB criteria. RESULTS: From July 2016 to June 2018, 3,698 samples from 72 VHA facilities were submitted for NGS testing, of which 3,182 samples (86%) were successfully sequenced. Most samples came from men with lung, prostate, and colorectal cancers. Thirty-four percent of samples were from patients who lived in a rural area. TP53, ATM, and KRAS were among the most commonly mutated genes. Approximately 70% of samples had at least one actionable mutation, with clinical trials identified as the recommended option in more than 50%. Mutations in genes associated with a neuroendocrine prostate cancer phenotype were expressed at increased frequency among veterans than in the general population. The most frequent therapies prescribed in response to NGS testing were immune checkpoint inhibitors, EGFR kinase inhibitors, and PARP inhibitors. CONCLUSION: Clinical implementation of precision oncology is feasible across the VHA health care system, including rural sites. Veterans have unique occupational exposures that might inform the nature of the mutational signatures identified here. Importantly, these results underscore the importance of increasing clinical trial availability to veterans.

Genome Sequence of Porphyromonas gingivalis Strain A7A1-28.

Porphyromonas gingivalis is an oral opportunistic pathogen. Sequenced P. gingivalis laboratory strains display limited diversity in antigens that modulate host responses. Here, we present the genome sequence of A7A1-28, a strain possessing atypical fimbrillin and capsule types, with a single contig of 2,249,024 bp and a G+C content of 48.58%.

Genome Sequence of Porphyromonas gingivalis Strain 381.

Porphyromonas gingivalis is associated with both oral and systemic diseases. Strain-specific P. gingivalis invasion phenotypes do not reliably predict disease presentation during in vivo studies. Here, we present the genome sequence of 381, a common laboratory strain, with a single contig of 2,378,872 bp and a G+C content of 48.36%.

Complete genome sequence of the Antarctic Halorubrum lacusprofundi type strain ACAM 34.

Halorubrum lacusprofundi is an extreme halophile within the archaeal phylum Euryarchaeota. The type strain ACAM 34 was isolated from Deep Lake, Antarctica. H. lacusprofundi is of phylogenetic interest because it is distantly related to the haloarchaea that have previously been sequenced. It is also of interest because of its psychrotolerance. We report here the complete genome sequence of H. lacusprofundi type strain ACAM 34 and its annotation. This genome is part of a 2006 Joint Genome Institute Community Sequencing Program project to sequence genomes of diverse Archaea.

Genome Sequence of Porphyromonas gingivalis Strain AJW4.

Porphyromonas gingivalis is associated with oral and systemic diseases. Strain-specific P. gingivalis invasion phenotypes have been correlated with disease presentation in infected laboratory animals. Here, we present the genome sequence of AJW4, a minimally invasive strain, with a single contig of 2,372,492 bp and a G+C content of 48.27%.

Genome Sequence of Porphyromonas gingivalis Strain A7436.

Porphyromonas gingivalis is strongly associated with periodontitis. P. gingivalis strain trafficking and tissue homing differ widely, even among presumptive closely related strains, such as W83 and A7436. Here, we present the genome sequence of A7436 with a single contig of 2,367,029 bp and a G+C content of 48.33%.

Deep-sea hydrothermal vent bacteria related to human pathogenic Vibrio species.

Vibrio species are both ubiquitous and abundant in marine coastal waters, estuaries, ocean sediment, and aquaculture settings worldwide. We report here the isolation, characterization, and genome sequence of a novel Vibrio species, Vibrio antiquarius, isolated from a mesophilic bacterial community associated with hydrothermal vents located along the East Pacific Rise, near the southwest coast of Mexico. Genomic and phenotypic analysis revealed V. antiquarius is closely related to pathogenic Vibrio species, namely Vibrio alginolyticus, Vibrio parahaemolyticus, Vibrio harveyi, and Vibrio vulnificus, but sufficiently divergent to warrant a separate species status. The V. antiquarius genome encodes genes and operons with ecological functions relevant to the environment conditions of the deep sea and also harbors factors known to be involved in human disease caused by freshwater, coastal, and brackish water vibrios. The presence of virulence factors in this deep-sea Vibrio species suggests a far more fundamental role of these factors for their bacterial host. Comparative genomics revealed a variety of genomic events that may have provided an important driving force in V. antiquarius evolution, facilitating response to environmental conditions of the deep sea.

Detection of Bacillus anthracis DNA in complex soil and air samples using next-generation sequencing.

Bacillus anthracis is the potentially lethal etiologic agent of anthrax disease, and is a significant concern in the realm of biodefense. One of the cornerstones of an effective biodefense strategy is the ability to detect infectious agents with a high degree of sensitivity and specificity in the context of a complex sample background. The nature of the B. anthracis genome, however, renders specific detection difficult, due to close homology with B. cereus and B. thuringiensis. We therefore elected to determine the efficacy of next-generation sequencing analysis and microarrays for detection of B. anthracis in an environmental background. We applied next-generation sequencing to titrated genome copy numbers of B. anthracis in the presence of background nucleic acid extracted from aerosol and soil samples. We found next-generation sequencing to be capable of detecting as few as 10 genomic equivalents of B. anthracis DNA per nanogram of background nucleic acid. Detection was accomplished by mapping reads to either a defined subset of reference genomes or to the full GenBank database. Moreover, sequence data obtained from B. anthracis could be reliably distinguished from sequence data mapping to either B. cereus or B. thuringiensis. We also demonstrated the efficacy of a microbial census microarray in detecting B. anthracis in the same samples, representing a cost-effective and high-throughput approach, complementary to next-generation sequencing. Our results, in combination with the capacity of sequencing for providing insights into the genomic characteristics of complex and novel organisms, suggest that these platforms should be considered important components of a biosurveillance strategy.

Complete genome sequence of Halorhodospira halophila SL1.

Halorhodospira halophila is among the most halophilic organisms known. It is an obligately photosynthetic and anaerobic purple sulfur bacterium that exhibits autotrophic growth up to saturated NaCl concentrations. The type strain H. halophila SL1 was isolated from a hypersaline lake in Oregon. Here we report the determination of its entire genome in a single contig. This is the first genome of a phototrophic extreme halophile. The genome consists of 2,678,452 bp, encoding 2,493 predicted genes as determined by automated genome annotation. Of the 2,407 predicted proteins, 1,905 were assigned to a putative function. Future detailed analysis of this genome promises to yield insights into the halophilic adaptations of this organism, its ability for photoautotrophic growth under extreme conditions, and its characteristic sulfur metabolism.

The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation.

BACKGROUND: The emergence of next generation sequencing (NGS) has provided the means for rapid and high throughput sequencing and data generation at low cost, while concomitantly creating a new set of challenges. The number of available assembled microbial genomes continues to grow rapidly and their quality reflects the quality of the sequencing technology used, but also of the analysis software employed for assembly and annotation. METHODOLOGY/PRINCIPAL FINDINGS: In this work, we have explored the quality of the microbial draft genomes across various sequencing technologies. We have compared the draft and finished assemblies of 133 microbial genomes sequenced at the Department of Energy-Joint Genome Institute and finished at the Los Alamos National Laboratory using a variety of combinations of sequencing technologies, reflecting the transition of the institute from Sanger-based sequencing platforms to NGS platforms. The quality of the public assemblies and of the associated gene annotations was evaluated using various metrics. Results obtained with the different sequencing technologies, as well as their effects on downstream processes, were analyzed. Our results demonstrate that the Illumina HiSeq 2000 sequencing system, the primary sequencing technology currently used for de novo genome sequencing and assembly at JGI, has various advantages in terms of total sequence throughput and cost, but it also introduces challenges for the downstream analyses. In all cases assembly results although on average are of high quality, need to be viewed critically and consider sources of errors in them prior to analysis. CONCLUSION: These data follow the evolution of microbial sequencing and downstream processing at the JGI from draft genome sequences with large gaps corresponding to missing genes of significant biological role to assemblies with multiple small gaps (Illumina) and finally to assemblies that generate almost complete genomes (Illumina+PacBio).

RegPrecise web services interface: programmatic access to the transcriptional regulatory interactions in bacteria reconstructed by comparative genomics.

Web services application programming interface (API) was developed to provide a programmatic access to the regulatory interactions accumulated in the RegPrecise database (http://regprecise.lbl.gov), a core resource on transcriptional regulation for the microbial domain of the Department of Energy (DOE) Systems Biology Knowledgebase. RegPrecise captures and visualize regulogs, sets of genes controlled by orthologous regulators in several closely related bacterial genomes, that were reconstructed by comparative genomics. The current release of RegPrecise 2.0 includes >1400 regulogs controlled either by protein transcription factors or by conserved ribonucleic acid regulatory motifs in >250 genomes from 24 taxonomic groups of bacteria. The reference regulons accumulated in RegPrecise can serve as a basis for automatic annotation of regulatory interactions in newly sequenced genomes. The developed API provides an efficient access to the RegPrecise data by a comprehensive set of 14 web service resources. The RegPrecise web services API is freely accessible at http://regprecise.lbl.gov/RegPrecise/services.jsp with no login requirements.

Temperature regulation of virulence factors in the pathogen Vibrio coralliilyticus.

Sea surface temperatures (SST) are rising because of global climate change. As a result, pathogenic Vibrio species that infect humans and marine organisms during warmer summer months are of growing concern. Coral reefs, in particular, are already experiencing unprecedented degradation worldwide due in part to infectious disease outbreaks and bleaching episodes that are exacerbated by increasing SST. For example, Vibrio coralliilyticus, a globally distributed bacterium associated with multiple coral diseases, infects corals at temperatures above 27 °C. The mechanisms underlying this temperature-dependent pathogenicity, however, are unknown. In this study, we identify potential virulence mechanisms using whole genome sequencing of V. coralliilyticus ATCC (American Type Culture Collection) BAA-450. Furthermore, we demonstrate direct temperature regulation of numerous virulence factors using proteomic analysis and bioassays. Virulence factors involved in motility, host degradation, secretion, antimicrobial resistance and transcriptional regulation are upregulated at the higher virulent temperature of 27 °C, concurrent with phenotypic changes in motility, antibiotic resistance, hemolysis, cytotoxicity and bioluminescence. These results provide evidence that temperature regulates multiple virulence mechanisms in V. coralliilyticus, independent of abundance. The ecological and biological significance of this temperature-dependent virulence response is reinforced by climate change models that predict tropical SST to consistently exceed 27 °C during the spring, summer and fall seasons. We propose V. coralliilyticus as a model Gram-negative bacterium to study temperature-dependent pathogenicity in Vibrio-related diseases.

Scenario driven data modelling: a method for integrating diverse sources of data and data streams.

BACKGROUND: Biology is rapidly becoming a data intensive, data-driven science. It is essential that data is represented and connected in ways that best represent its full conceptual content and allows both automated integration and data driven decision-making. Recent advancements in distributed multi-relational directed graphs, implemented in the form of the Semantic Web make it possible to deal with complicated heterogeneous data in new and interesting ways. RESULTS: This paper presents a new approach, scenario driven data modelling (SDDM), that integrates multi-relational directed graphs with data streams. SDDM can be applied to virtually any data integration challenge with widely divergent types of data and data streams. In this work, we explored integrating genetics data with reports from traditional media. SDDM was applied to the New Delhi metallo-beta-lactamase gene (NDM-1), an emerging global health threat. The SDDM process constructed a scenario, created a RDF multi-relational directed graph that linked diverse types of data to the Semantic Web, implemented RDF conversion tools (RDFizers) to bring content into the Sematic Web, identified data streams and analytical routines to analyse those streams, and identified user requirements and graph traversals to meet end-user requirements. CONCLUSIONS: We provided an example where SDDM was applied to a complex data integration challenge. The process created a model of the emerging NDM-1 health threat, identified and filled gaps in that model, and constructed reliable software that monitored data streams based on the scenario derived multi-relational directed graph. The SDDM process significantly reduced the software requirements phase by letting the scenario and resulting multi-relational directed graph define what is possible and then set the scope of the user requirements. Approaches like SDDM will be critical to the future of data intensive, data-driven science because they automate the process of converting massive data streams into usable knowledge.

Genome sequence of the ethanol-producing Zymomonas mobilis subsp. pomaceae lectotype strain ATCC 29192.

Zymomonas mobilis is an alphaproteobacterium studied for bioethanol production. Different strains of this organism have been hitherto sequenced; they all belong to the Z. mobilis subsp. mobilis taxon. Here we report the finished and annotated genome sequence of strain ATCC 29192, a cider-spoiling agent isolated in the United Kingdom. ATCC 29192 is the lectotype of the second-best-characterized subspecies of Z. mobilis, Z. mobilis subsp. pomaceae. The nucleotide sequence of ATCC 29192 deviates from that of Z. mobilis subsp. mobilis representatives, which justifies its distinct taxonomic positioning and proves particularly useful for comparative and functional genomic analyses.

Genome sequence of the ethanol-producing Zymomonas mobilis subsp. mobilis lectotype strain ATCC 10988.

Zymomonas mobilis ATCC 10988 is the type strain of the Z. mobilis subsp. mobilis taxon, members of which are some of the most rigorous ethanol-producing bacteria. Isolated from Agave cactus fermentations in Mexico, ATCC 10988 is one of the first Z. mobilis strains to be described and studied. Its robustness in sucrose-substrate fermentations, physiological characteristics, large number of plasmids, and overall genomic plasticity render this strain important to the study of the species. Here we report the finishing and annotation of the ATCC 10988 chromosomal and plasmid genome.

Complete genome sequence of the anaerobic, halophilic alkalithermophile Natranaerobius thermophilus JW/NM-WN-LF.

The genome of the anaerobic halophilic alkalithermophile Natranaerobius thermophilus consists of one 3,165,557-bp chromosome and two plasmids (17,207 bp and 8,689 bp). The present study is the first to report the completely sequenced genome of an anaerobic polyextremophile and genes associated with roles in regulation of intracellular osmotic pressure, pH homeostasis, and growth at elevated temperatures.

Genome Sequence of the ethene- and vinyl chloride-oxidizing actinomycete Nocardioides sp. strain JS614.

Nocardioides sp. strain JS614 grows on ethene and vinyl chloride (VC) as sole carbon and energy sources and is of interest for bioremediation and biocatalysis. Sequencing of the complete genome of JS614 provides insight into the genetic basis of alkene oxidation, supports ongoing research into the physiology and biochemistry of growth on ethene and VC, and provides biomarkers to facilitate detection of VC/ethene oxidizers in the environment. This is the first genome sequence from the genus Nocardioides and the first genome of a VC/ethene-oxidizing bacterium.

Genome sequence of "Pedosphaera parvula" Ellin514, an aerobic Verrucomicrobial isolate from pasture soil.

"Pedosphaera parvula" Ellin514 is an aerobically grown verrucomicrobial isolate from pasture soil. It is one of the few cultured representatives of subdivision 3 of the phylum Verrucomicrobia. Members of this group are widespread in terrestrial environments.