The Promises and Pitfalls of Machine Learning for Detecting Viruses in Aquatic Metagenomes

Tools allowing for the identification of viral sequences in host-associated and environmental metagenomes allows for a better understanding of the genetics and ecology of viruses and their hosts. Recently, new approaches using machine learning methods to distinguish viral from bacterial signal using k-mer sequence signatures were published for identifying viral contigs in metagenomes. The promise of these content-based approaches is the ability to discover new viruses, with no or few known relatives. In this perspective paper, we examine the use of the content-based machine learning tool VirFinder for the identification of viral sequences in aquatic metagenomes and explore the possibility of using ecosystem-focused models targeted to marine metagenomes. We discuss the impact of the training set composition on the tool performance and the current limitation for the retrieval of low abundance viral sequences in metagenomes. We identify potential biases that could arise from machine learning approaches for viral hunting in real-world datasets and suggest possible avenues to overcome them

The Promises and Pitfalls of Machine Learning for Detecting Viruses in Aquatic Metagenomes

Tools allowing for the identification of viral sequences in host-associated and environmental metagenomes allows for a better understanding of the genetics and ecology of viruses and their hosts. Recently, new approaches using machine learning methods to distinguish viral from bacterial signal using k-mer sequence signatures were published for identifying viral contigs in metagenomes. The promise of these content-based approaches is the ability to discover new viruses, with no or few known relatives. In this perspective paper, we examine the use of the content-based machine learning tool VirFinder for the identification of viral sequences in aquatic metagenomes and explore the possibility of using ecosystem-focused models targeted to marine metagenomes. We discuss the impact of the training set composition on the tool performance and the current limitation for the retrieval of low abundance viral sequences in metagenomes. We identify potential biases that could arise from machine learning approaches for viral hunting in real-world datasets and suggest possible avenues to overcome them.National Science Foundation [1640775]Open access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Metabolic reprogramming by viruses in the sunlit and dark ocean

BACKGROUND:Marine ecosystem function is largely determined by matter and energy transformations mediated by microbial community interaction networks. Viral infection modulates network properties through mortality, gene transfer and metabolic reprogramming.RESULTS:Here we explore the nature and extent of viral metabolic reprogramming throughout the Pacific Ocean depth continuum. We describe 35 marine viral gene families with potential to reprogram metabolic flux through central metabolic pathways recovered from Pacific Ocean waters. Four of these families have been previously reported but 31 are novel. These known and new carbon pathway auxiliary metabolic genes were recovered from a total of 22 viral metagenomes in which viral auxiliary metabolic genes were differentiated from low-level cellular DNA inputs based on small subunit ribosomal RNA gene content, taxonomy, fragment recruitment and genomic context information. Auxiliary metabolic gene distribution patterns reveal that marine viruses target overlapping, but relatively distinct pathways in sunlit and dark ocean waters to redirect host carbon flux towards energy production and viral genome replication under low nutrient, niche-differentiated conditions throughout the depth continuum.CONCLUSIONS:Given half of ocean microbes are infected by viruses at any given time, these findings of broad viral metabolic reprogramming suggest the need for renewed consideration of viruses in global ocean carbon models.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

Libra: scalable k-mer-based tool for massive all-vs-all metagenome comparisons

Background Shotgun metagenomics provides powerful insights into microbial community biodiversity and function. Yet, inferences from metagenomic studies are often limited by dataset size and complexity and are restricted by the availability and completeness of existing databases. De novo comparative metagenomics enables the comparison of metagenomes based on their total genetic content. Results We developed a tool called Libra that performs an all-vs-all comparison of metagenomes for precise clustering based on their k-mer content. Libra uses a scalable Hadoop framework for massive metagenome comparisons, Cosine Similarity for calculating the distance using sequence composition and abundance while normalizing for sequencing depth, and a web-based implementation in iMicrobe (http://imicrobe.us) that uses the CyVerse advanced cyberinfrastructure to promote broad use of the tool by the scientific community. Conclusions A comparison of Libra to equivalent tools using both simulated and real metagenomic datasets, ranging from 80 million to 4.2 billion reads, reveals that methods commonly implemented to reduce compute time for large datasets, such as data reduction, read count normalization, and presence/absence distance metrics, greatly diminish the resolution of large-scale comparative analyses. In contrast, Libra uses all of the reads to calculate k-mer abundance in a Hadoop architecture that can scale to any size dataset to enable global-scale analyses and link microbial signatures to biological processes.National Science Foundation [1640775]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Integration of hybridization-based markers (overgos) into physical maps for comparative and evolutionary explorations in the genus Oryza and in Sorghum

BACKGROUND: With the completion of the genome sequence for rice (Oryza sativa L.), the focus of rice genomics research has shifted to the comparison of the rice genome with genomes of other species for gene cloning, breeding, and evolutionary studies. The genus Oryza includes 23 species that shared a common ancestor 8–10 million years ago making this an ideal model for investigations into the processes underlying domestication, as many of the Oryza species are still undergoing domestication. This study integrates high-throughput, hybridization-based markers with BAC end sequence and fingerprint data to construct physical maps of rice chromosome 1 orthologues in two wild Oryza species. Similar studies were undertaken in Sorghum bicolor, a species which diverged from cultivated rice 40–50 million years ago. RESULTS: Overgo markers, in conjunction with fingerprint and BAC end sequence data, were used to build sequence-ready BAC contigs for two wild Oryza species. The markers drove contig merges to construct physical maps syntenic to rice chromosome 1 in the wild species and provided evidence for at least one rearrangement on chromosome 1 of the O. sativa versus Oryza officinalis comparative map. When rice overgos were aligned to available S. bicolor sequence, 29% of the overgos aligned with three or fewer mismatches; of these, 41% gave positive hybridization signals. Overgo hybridization patterns supported colinearity of loci in regions of sorghum chromosome 3 and rice chromosome 1 and suggested that a possible genomic inversion occurred in this syntenic region in one of the two genomes after the divergence of S. bicolor and O. sativa. CONCLUSION: The results of this study emphasize the importance of identifying conserved sequences in the reference sequence when designing overgo probes in order for those probes to hybridize successfully in distantly related species. As interspecific markers, overgos can be used successfully to construct physical maps in species which diverged less than 8 million years ago, and can be used in a more limited fashion to examine colinearity among species which diverged as much as 40 million years ago. Additionally, overgos are able to provide evidence of genomic rearrangements in comparative physical mapping studies

Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition

A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009–2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world’s planktonic ecosystems

Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition

A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009-2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, www.ebi.ac.uk/ena). The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world's planktonic ecosystems

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Viral community dynamics and functional specialization in the Pacific Ocean

Viruses are the most abundant biological entity on Earth and outnumber their hosts ten-to-one. Ocean viruses (phages) impact bacterial-driven global biogeochemical cycles through lysis, manipulating host metabolism, and horizontal gene transfer. However, knowledge of virus-host interactions and viral roles in ecosystems remains limited due to few cultured marine phage genomes and non-quantitative culture-independent metagenomes. Here, I develop and apply novel and well-tested bioinformatic techniques to explore Pacific Ocean viral communities using quantitative datasets derived from rigorously-tested preparation methods. To evaluate concentration and purification methods, I examined triplicate metagenomes from a single ocean sample using four protocols. Concentration protocols showed statistical differences in taxonomy whereas purification protocols did not. Specifically, TFF-concentrated metagenomes contained trace bacterial contamination and had fewer abundant taxa as compared to FeCl3-precipitated metagenomes. K-mer analysis using the complete dataset revealed polymerase choice defined access to "rare" sequences. To explore unknown viral sequences, I organized known and unknown sequence space into 27K high-confidence protein clusters (PCs) from 32 diverse Pacific Ocean Virus (POV) metagenomes, which doubled available PCs and included the first pelagic deep-sea viral metagenomes. Using PCs as a whole-viral-community diversity metric revealed decreases from coastal to open ocean, winter to summer, and deep to surface, that correlate with data from microbial genetic diversity markers (no parallel viral markers exist). Biologically, POV metagenomes showed that viruses likely reprogram central metabolic pathways in microbial communities far beyond the "photosynthesis viruses" paradigm. Gene distribution patterns from 35 viral gene families (31 new) revealed niche-specific (photic vs aphotic zone) altered pathway carbon flux presumably optimized to best locally generate energy and drive viral replication. Further, these PCs define the first "core" (180 genes) and "flexible" (423K genes total) viral community genome. Functionally, core genes again suggest niche-differentation with extensive Fe-S cluster-related genes for electron transport and metabolic enzyme catalysis in photic samples, and manipulation of host pressure-sensitive genes in aphotic samples. Taxonomically, these data deconstruct the culture-based paradigm that tailed viruses dominate in the wild - instead they appear ubiquitous, but not abundant