CropPol: A dynamic, open and global database on crop pollination.

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-2005 (21 studies), 2006-2010 (40), 2011-2015 (88), and 2016-2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA).

Advanced MRI of Liver Fibrosis and Treatment Response in a Rat Model of Nonalcoholic Steatohepatitis.

Background Liver biopsy is the reference standard to diagnose nonalcoholic steatohepatitis (NASH) but is invasive with potential complications. Purpose To evaluate molecular MRI with type 1 collagen-specific probe EP-3533 and allysine-targeted fibrogenesis probe Gd-Hyd, MR elastography, and native T1 to characterize fibrosis and to assess treatment response in a rat model of NASH. Materials and Methods MRI was performed prospectively (June-November 2018) in six groups of male Wistar rats (a) age- and (b) weight-matched animals received standard chow (n = 12 per group); (c) received choline-deficient, l-amino acid-defined, high-fat diet (CDAHFD) for 6 weeks or (d) 9 weeks (n = 8 per group); (e) were fed 6 weeks of CDAHFD and switched to standard chow for 3 weeks (n = 12); (f) were fed CDAHFD for 9 weeks with daily treatment of elafibranor beginning at week 6 (n = 14). Differences in imaging measurements and tissue analyses among groups were tested with one-way analysis of variance. The ability of each imaging measurement to stage fibrosis was quantified by using area under the receiver operating characteristic curve (AUC) with quantitative digital pathology (collagen proportionate area [CPA]) as reference standard. Optimal cutoff values for distinguishing advanced fibrosis were used to assess treatment response. Results AUC for distinguishing fibrotic (CPA >4.8%) from nonfibrotic (CPA ≤4.8%) livers was 0.95 (95% confidence interval [CI]: 0.91, 1.00) for EP-3533, followed by native T1, Gd-Hyd, and MR elastography with AUCs of 0.90 (95% CI: 0.83, 0.98), 0.84 (95% CI: 0.74, 0.95), and 0.65 (95% CI: 0.51, 0.79), respectively. AUCs for discriminating advanced fibrosis (CPA >10.3%) were 0.86 (95% CI: 0.76, 0.97), 0.96 (95% CI: 0.90, 1.01), 0.84 (95% CI: 0.70, 0.98), and 0.74 (95% CI: 0.63, 0.86) for EP-3533, Gd-Hyd, MR elastography, and native T1, respectively. Gd-Hyd MRI had the highest accuracy (24 of 26, 92%; 95% CI: 75%, 99%) in identifying responders and nonresponders in the treated groups compared with MR elastography (23 of 26, 88%; 95% CI: 70%, 98%), EP-3533 (20 of 26, 77%; 95% CI: 56%, 91%), and native T1 (14 of 26, 54%; 95% CI: 33%, 73%). Conclusion Collagen-targeted molecular MRI most accurately detected early onset of fibrosis, whereas the fibrogenesis probe Gd-Hyd proved most accurate for detecting treatment response. © RSNA, 2020 Online supplemental material is available for this article.

Gut Microbiota-Derived Tryptophan Metabolites Modulate Inflammatory Response in Hepatocytes and Macrophages.

The gut microbiota plays a significant role in the progression of fatty liver disease; however, the mediators and their mechanisms remain to be elucidated. Comparing metabolite profile differences between germ-free and conventionally raised mice against differences between mice fed a low- and high-fat diet (HFD), we identified tryptamine and indole-3-acetate (I3A) as metabolites that depend on the microbiota and are depleted under a HFD. Both metabolites reduced fatty-acid- and LPS-stimulated production of pro-inflammatory cytokines in macrophages and inhibited the migration of cells toward a chemokine, with I3A exhibiting greater potency. In hepatocytes, I3A attenuated inflammatory responses under lipid loading and reduced the expression of fatty acid synthase and sterol regulatory element-binding protein-1c. These effects were abrogated in the presence of an aryl-hydrocarbon receptor (AhR) antagonist, indicating that the effects are AhR dependent. Our results suggest that gut microbiota could influence inflammatory responses in the liver through metabolites engaging host receptors.

Biologically Consistent Annotation of Metabolomics Data.

Annotation of metabolites remains a major challenge in liquid chromatography-mass spectrometry (LC-MS) based untargeted metabolomics. The current gold standard for metabolite identification is to match the detected feature with an authentic standard analyzed on the same equipment and using the same method as the experimental samples. However, there are substantial practical challenges in applying this approach to large data sets. One widely used annotation approach is to search spectral libraries in reference databases for matching metabolites; however, this approach is limited by the incomplete coverage of these libraries. An alternative computational approach is to match the detected features to candidate chemical structures based on their mass and predicted fragmentation pattern. Unfortunately, both of these approaches can match multiple identities with a single feature. Another issue is that annotations from different tools often disagree. This paper presents a novel LC-MS data annotation method, termed Biologically Consistent Annotation (BioCAn), that combines the results from database searches and in silico fragmentation analyses and places these results into a relevant biological context for the sample as captured by a metabolic model. We demonstrate the utility of this approach through an analysis of CHO cell samples. The performance of BioCAn is evaluated against several currently available annotation tools, and the accuracy of BioCAn annotations is verified using high-purity analytical standards.

Non-bee insects are important contributors to global crop pollination.

Wild and managed bees are well documented as effective pollinators of global crops of economic importance. However, the contributions by pollinators other than bees have been little explored despite their potential to contribute to crop production and stability in the face of environmental change. Non-bee pollinators include flies, beetles, moths, butterflies, wasps, ants, birds, and bats, among others. Here we focus on non-bee insects and synthesize 39 field studies from five continents that directly measured the crop pollination services provided by non-bees, honey bees, and other bees to compare the relative contributions of these taxa. Non-bees performed 25-50% of the total number of flower visits. Although non-bees were less effective pollinators than bees per flower visit, they made more visits; thus these two factors compensated for each other, resulting in pollination services rendered by non-bees that were similar to those provided by bees. In the subset of studies that measured fruit set, fruit set increased with non-bee insect visits independently of bee visitation rates, indicating that non-bee insects provide a unique benefit that is not provided by bees. We also show that non-bee insects are not as reliant as bees on the presence of remnant natural or seminatural habitat in the surrounding landscape. These results strongly suggest that non-bee insect pollinators play a significant role in global crop production and respond differently than bees to landscape structure, probably making their crop pollination services more robust to changes in land use. Non-bee insects provide a valuable service and provide potential insurance against bee population declines.

Pathways and functions of gut microbiota metabolism impacting host physiology.

The bacterial populations in the human intestine impact host physiological functions through their metabolic activity. In addition to performing essential catabolic and biotransformation functions, the gut microbiota produces bioactive small molecules that mediate interactions with the host and contribute to the neurohumoral axes connecting the intestine with other parts of the body. This review discusses recent progress in characterizing the metabolic products of the gut microbiota and their biological functions, focusing on studies that investigate the responsible bacterial pathways and cognate host receptors. Several key areas are highlighted for future development: context-based analysis targeting pathways; integration of analytical approaches; metabolic modeling; and synthetic systems for in vivo manipulation of microbiota functions. Prospectively, these developments could further our mechanistic understanding of host-microbiota interactions.

Wild pollinators enhance fruit set of crops regardless of honey bee abundance.

The diversity and abundance of wild insect pollinators have declined in many agricultural landscapes. Whether such declines reduce crop yields, or are mitigated by managed pollinators such as honey bees, is unclear. We found universally positive associations of fruit set with flower visitation by wild insects in 41 crop systems worldwide. In contrast, fruit set increased significantly with flower visitation by honey bees in only 14% of the systems surveyed. Overall, wild insects pollinated crops more effectively; an increase in wild insect visitation enhanced fruit set by twice as much as an equivalent increase in honey bee visitation. Visitation by wild insects and honey bees promoted fruit set independently, so pollination by managed honey bees supplemented, rather than substituted for, pollination by wild insects. Our results suggest that new practices for integrated management of both honey bees and diverse wild insect assemblages will enhance global crop yields.

Regulation of axon guidance by slit and netrin signaling in the Drosophila ventral nerve cord.

Netrin and Slit signaling systems play opposing roles during the positioning of longitudinal tracts along the midline in the ventral nerve cord of Drosophila embryo. It has been hypothesized that a gradient of Slit from the midline interacts with three different Robo receptors to specify the axon tract positioning. However, no such gradient has been detected. Moreover, overexpression of Slit at the midline has no effect on the positioning of these lateral tracts. In this article, we show that Slit is present outside of the midline along the longitudinal and commissural tracts. Sli from the midline, in a Robo-independent manner, is initially taken up by the commissural axon tracts when they cross the midline and is transported along the commissural tracts into the longitudinal connectives. These results are not consistent with a Sli gradient model. We also find that sli mRNA is maternally deposited and embryos that are genetically null for sli can have weaker guidance defects. Moreover, in robo or robo3 mutants, embryos with normal axon tracts are found and such robo embryos reach pupal stages and die, while robo3 mutant embryos develop into normal individuals and produce eggs. Interestingly, embryos from robo3 homozygous individuals fail to develop but have axon tracts ranging from normal to various defects: robo3 phenotype, robo phenotype, and slit-like phenotype, suggesting a more complex functional role for these genes than what has been proposed. Finally, our previous results indicated that netrin phenotype is epistatic to sli or robo phenotypes. However, it seems likely that this previously reported epistatic relationship might be due to the partial penetrance of the sli, robo, robo3 (or robo2) phenotypes. Our results argue that double mutant epistasis is most definitive only if the penetrance of the phenotypes of the mutants involved is complete.