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Endo, H.

Publications and source records attributed to Endo, H..

40 records · Page 3Linked to original sources

Quantitative assessment of NCLDV-host interactions predicted by co-occurrence analyses

Nucleocytoplasmic DNA viruses (NCLDVs) are highly diverse and abundant in marine environments. However, knowledge of their hosts is limited because only a few NCLDVs have been isolated so far. Taking advantage of the recent large-scale marine metagenomics census, in silico host prediction approaches are expected to fill the gap and further expand our knowledge of virus-host relationships for unknown NCLDVs. In this study, we built co-occurrence networks of NCLDVs and eukaryotic taxa to predict virus-host interactions using Tara Oceans sequencing data. Using the positive likelihood ratio to assess the performance of host prediction for NCLDVs, we benchmarked several co-occurrence approaches and demonstrated an increase in the odds ratio of predicting true positive relationships four-fold compared with random host predictions. To further refine host predictions from high-dimensional co-occurrence networks, we developed a phylogeny-informed filtering method, Taxon Interaction Mapper, and showed it further improved the prediction performance by twelve-fold. Finally, we inferred virophage - NCLDV networks to corroborate that co-occurrence approaches are effective for predicting interacting partners of NCLDVs in marine environments. ImportanceNCLDVs can infect a wide range of eukaryotes although their life cycle is less dependent on hosts compared with other viruses. However, our understanding of NCLDV- host systems is highly limited because few of these viruses have been isolated so far. Co-occurrence information has been assumed to be useful to predict virus-host interactions. In this study, we quantitatively show the effectiveness of co-occurrence inference for NCLDV host prediction. We also improve the prediction performance with a phylogeny-guided method, which leads to a concise list of candidate host lineages for three NCLDV families. Our results underpin the usage of co-occurrence approach for metagenomic exploration of the ecology of this diverse group of viruses.

microbiology↗

The two-step chemosensory system underlying the oligophagy of silkworm larvae

Oligophagous insect herbivores specifically identify host-plant leaves using their keen sense of taste1. Plant secondary metabolites and sugars are key chemical cues for insects to identify host plants and evaluate their nutritional value, respectively2. However, it is poorly understood how the insect chemosensory system integrates the information from various gustatory inputs. Here we report that a two-step chemosensory system is responsible for host acceptance by larvae of the silkworm Bombyx mori, a specialist for several mulberry species. The first step controlled by a gustatory organ, the maxillary palp (MP), is host-plant recognition during palpation at the leaf edge. Surprisingly, MP detects chlorogenic acid, quercetin glycosides, and {beta}-sitosterol, which stimulate feeding by the silkworm3-6, with ultra-sensitivity (thresholds of aM to fM). Detecting a mixture of these compounds triggers test biting. The second step is evaluation of the sugar content in the leaf sap exuded by test biting. Low-sensitivity chemosensory neurons in another gustatory organ, the maxillary galea (MG), mainly detect sucrose in the leaf sap exuded by test biting, allowing larvae to accept the leaf and proceed to persistent biting. Our present work shows the behavioral and neuronal basis of host acceptance in the silkworm, mainly driven by six phytochemicals. It also reveals that the ultra-sensitive gustation via MP strictly limits initiation of feeding in the silkworm unless it detects a certain combination of host compounds, suggesting an essential role of MP in host-plant selection. The two-step chemosensory system reported herein may commonly underlie stereotyped feeding behavior in phytophagous insects and determine their feeding habits.

ecology↗

Viruses of the eukaryotic plankton are predicted to increase carbon export efficiency in the global sunlit ocean

The biological carbon pump, in which carbon fixed by photosynthesis is exported to the deep ocean through sinking, is a major process in Earths carbon cycle. The proportion of primary production that is exported is termed the carbon export efficiency (CEE). Based on in-lab or regional scale observations, viruses were previously suggested to affect the CEE (i.e., viral "shunt" and "shuttle"). In this study, we tested associations between viral community composition and CEE measured at a global scale. A regression model based on relative abundance of viral marker genes explained 67% of the variation in CEE. Viruses with high importance in the model were predicted to infect ecologically important hosts. These results are consistent with the view that the viral shunt and shuttle functions at a large scale and further imply that viruses likely act in this process in a way dependent on their hosts and ecosystem dynamics.

ecology↗

KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold

SummaryKofamKOALA is a web server to assign KEGG Orthologs (KOs) to protein sequences by homology search against a database of profile hidden Markov models (KOfam) with pre-computed adaptive score thresholds. KofamKOALA is faster than existing KO assignment tools with its accuracy being comparable to the best performing tools. Function annotation by KofamKOALA helps linking genes to KEGG resources such as the KEGG pathway maps and facilitates molecular network reconstruction.\n\nAvailabilityKofamKOALA, KofamScan, and KOfam are freely available from https://www.genome.jp/tools/kofamkoala/\n\nContactogata@kuicr.kyoto-u.ac.jp

bioinformatics↗