Continental-Scale Paddy Soil Bacterial Community Structure, Function, and Biotic Interaction.

Rice paddy soil-associated microbiota participate in biogeochemical processes that underpin rice yield and soil sustainability, yet continental-scale biogeographic patterns of paddy soil microbiota remain elusive. The soil bacteria of four typical Chinese rice-growing regions were characterized and compared to those of nonpaddy soils. The paddy soil bacteria were significantly less diverse, with unique taxonomic and functional composition, and harbored distinct cooccurrence network topology. Both stochastic and deterministic processes shaped soil bacteria assembly, but paddy samples exhibited a stronger deterministic signature than nonpaddy samples. Compared to other environmental factors, climatic factors such as mean monthly precipitation and mean annual temperature described most of the variance in soil bacterial community structure. Cooccurrence network analysis suggests that the continental biogeographic variance in bacterial community structure was described by the competition between two mutually exclusive bacterial modules in the community. Keystone taxa identified in network models (Anaerolineales, Ignavibacteriae, and Deltaproteobacteria) were more sensitive to changes in environmental factors, leading us to conclude that environmental factors may influence paddy soil bacterial communities via these keystone taxa. Characterizing the uniqueness of bacterial community patterns in paddy soil (compared to nonpaddy soils) at continental scales is central to improving crop productivity and resilience and to sustaining agricultural soils. IMPORTANCE Rice fields provide food for over half of the world's human population. The ecology of paddy soil microbiomes is shaped by human activities, which can have a profound impact on rice yield, greenhouse gas emissions, and soil health. Investigations of the soil bacteria in four typical Chinese rice-growing regions showed that (i) soil bacterial communities maintain highly modularized species-to-species network structures; (ii) community patterns were shaped by the balance of integrated stochastic and deterministic processes, in which homogenizing selection and dispersal limitation dominate; and (iii) deterministic processes and climatic and edaphic factors influence community patterns mainly by their impact on highly connected nodes (i.e., keystone taxa) in networks. Characterizing the unique ecology of bacterial community patterns in paddy soil at a continental scale may lead to improved crop productivity and resilience, as well as sustaining agricultural soils.

PSANet: Pyramid Splitting and Aggregation Network for 3D Object Detection in Point Cloud.

3D object detection in LiDAR point clouds has been extensively used in autonomous driving, intelligent robotics, and augmented reality. Although the one-stage 3D detector has satisfactory training and inference speed, there are still some performance problems due to insufficient utilization of bird's eye view (BEV) information. In this paper, a new backbone network is proposed to complete the cross-layer fusion of multi-scale BEV feature maps, which makes full use of various information for detection. Specifically, our proposed backbone network can be divided into a coarse branch and a fine branch. In the coarse branch, we use the pyramidal feature hierarchy (PFH) to generate multi-scale BEV feature maps, which retain the advantages of different levels and serves as the input of the fine branch. In the fine branch, our proposed pyramid splitting and aggregation (PSA) module deeply integrates different levels of multi-scale feature maps, thereby improving the expressive ability of the final features. Extensive experiments on the challenging KITTI-3D benchmark show that our method has better performance in both 3D and BEV object detection compared with some previous state-of-the-art methods. Experimental results with average precision (AP) prove the effectiveness of our network.

EPGNet: Enhanced Point Cloud Generation for 3D Object Detection.

Three-dimensional object detection from point cloud data is becoming more and more significant, especially for autonomous driving applications. However, it is difficult for lidar to obtain the complete structure of an object in a real scene due to its scanning characteristics. Although the existing methods have made great progress, most of them ignore the prior information of object structure, such as symmetry. So, in this paper, we use the symmetry of the object to complete the missing part in the point cloud and then detect it. Specifically, we propose a two-stage detection framework. In the first stage, we adopt an encoder-decoder structure to generate the symmetry points of the foreground points and make the symmetry points and the non-empty voxel centers form an enhanced point cloud. In the second stage, the enhanced point cloud is input into the baseline, which is an anchor-based region proposal network, to generate the detection results. Extensive experiments on the challenging KITTI benchmark show the effectiveness of our method, which has better performance on both 3D and BEV (bird's eye view) object detection compared with some previous state-of-the-art methods.

Black soldier fly larvae (Hermetia illucens) strengthen the metabolic function of food waste biodegradation by gut microbiome.

Vermicomposting using black soldier fly (BSF) larvae (Hermetia illucens) has gradually become a promising biotechnology for waste management, but knowledge about the larvae gut microbiome is sparse. In this study, 16S rRNA sequencing, SourceTracker, and network analysis were leveraged to decipher the influence of larvae gut microbiome on food waste (FW) biodegradation. The microbial community structure of BSF vermicompost (BC) changed greatly after larvae inoculation, with a peak colonization traceable to gut bacteria of 66.0%. The relative abundance of 11 out of 21 metabolic function groups in BC were significantly higher than that in natural composting (NC), such as carbohydrate-active enzymes. In addition, 36.5% of the functional genes in BC were significantly higher than those in NC. The changes of metabolic functions and functional genes were significantly correlated with the microbial succession. Moreover, the bacteria that proliferated in vermicompost, including Corynebacterium, Vagococcus, and Providencia, had strong metabolic abilities. Systematic and complex interactions between the BSF gut and BC bacteria occurred over time through invasion, altered the microbial community structure, and thus evolved into a new intermediate niche favourable for FW biodegradation. The study highlights BSF gut microbiome as an engine for FW bioconversion, which is conducive to bioproducts regeneration from wastes.

Characterization of enhancer trap and gene trap harboring Ac/Ds transposon in transgenic rice.

Insertion mutagenesis has become one of the most popular methods for gene functions analysis. Here we report a two-element Ac/Ds transposon system containing enhancer trap and gene trap for gene tagging in rice. The excision of Ds element was examined by PCR amplification. The excision frequency of Ds element varied from 0% to 40% among 20 F(2) populations derived from 11 different Ds parents. Southern blot analysis revealed that more than 70% of excised Ds elements reinserted into rice genome and above 70% of the reinserted Ds elements were located at different positions of the chromosome in rice. The result of histochemical GUS analysis indicated that 28% of enhancer trap and 22% of gene trap tagging plants displayed GUS activity in leaves, roots, flowers or seeds. The GUS positive lines will be useful for identifying gene function in rice.

Distribution and characterization of over 1000 T-DNA tags in rice genome.

We generated T-DNA insertions throughout the rice genome for saturation mutagenesis. More than 1,000 flanking sequences were mapped on 12 rice chromosomes. Our results showed that T-DNA tags were not randomly spread on rice chromosomes and were preferentially inserted in gene-rich regions. Few insertions (2.4%) were found in repetitive regions. T-DNA insertions in genic (58.1%) and intergenic regions (41.9%) showed a good correlation with the predicted size distribution of these sequences in the rice genome. Whereas, obvious biases were found for the insertions in the 5'- and 3'-regulatory regions outside the coding regions both at 500-bp size and in introns rather than in exons. Such distribution patterns and biases for T-DNA integration in rice are similar to that of the previous report in Arabidopsis, which may result from T-DNA integration mechanism itself. Rice will require approximately the same number of T-DNA insertions for saturation mutagenesis as will Arabidopsis. A database of the T-DNA insertion sites in rice is publicly available at our web site (http://www.genomics.zju.edu.cn/ricetdna).

[Application of Ac/Ds transposon system to genetate marker gene free transgenic plants in rice].

It is critical to generate marker gene free transgenic plants for retransformating or eliminating the potential harmfulness of marker gene and its product. In this study, Ac/Ds transposon system was developed for removal of hpt selection marker gene to obtain marker-free transgenic plants in rice ( Oryza sativa L.). Ds element containing the interesting gene bar was constructed next to the selection marker gene hpt to get Ds-T-DNA. Rice plants were transformed by Agrobacterium tumefaciens EHA105 containing Ac-T-DNA and Ds-T-DNA respectively. Rice plant containing single copy Ac-T-DNA was crossed with plant containing single copy Ds-T-DNA to obtain the F1 plant containing both Ac and Ds elements. F1 plant was self-crossed to produce F2 progeny in which T-DNA insert and transposed Ds element segregated independently. Two plants contained Ds element but no hpt marker gene in total 100 F2 plants. The result indicated that Ac/Ds transposon system could be used as a vector system for generating marker gene free transgenic plants in rice.