The Microbiome Protocols eBook (MPB) serves as a crucial bridge, filling gaps in microbiome protocols for both wet experiments and data analysis. The first edition, launched in 2020, featured 152 meticulously curated protocols, garnering widespread acclaim. We now extend a sincere invitation to researchers to participate in the upcoming 2nd version of MPB, contributing their valuable protocols to advance microbiome research.

The advent of next-generation sequencing has revolutionized microbiome research, enabling in-depth exploration of microbial communities through amplicon sequencing. The widespread adoption of sequencing across diverse fields, coupled with decreasing costs, underscores the critical need for validated, fully automated, reproducible, and adaptable analysis pipelines. However, analyzing these high-throughput datasets often necessitates extensive bioinformatics expertize, hindering accessibility for many researchers. To address this challenge, in 2023 we developed EasyAmplicon, a comprehensive, user-friendly pipeline that integrates popular tools such as USEARCH and VSEARCH, offering a streamlined workflow from raw data to results. Remarkably, EasyAmplicon has garnered significant recognition within a year, as evidenced by 127 citations to date. To further facilitate the researchers and enhance usability, we present a detailed protocol with a video recording that guides users through each step of the pipeline, including data preprocessing (quality filtering, chimera removal), amplicon sequence variant analysis, diversity analysis, and data visualization. The protocol is designed for ease of use, with each step documented, allowing researchers to execute the workflow without requiring complex scripting skills. The EasyAmplicon pipeline is freely available on GitHub ( https://github.com/YongxinLiu/EasyAmplicon ).

It is difficult for beginners to learn and use amplicon analysis software because there are so many software tools to choose from, and all of them need multiple steps of operation. Herein, we provide a cross-platform, open-source, and community-supported analysis pipeline EasyAmplicon. EasyAmplicon has most of the modules needed for an amplicon analysis, including data quality control, merging of paired-end reads, dereplication, clustering or denoising, chimera detection, generation of feature tables, taxonomic diversity analysis, compositional analysis, biomarker discovery, and publication-quality visualization. EasyAmplicon includes more than 30 cross-platform modules and R packages commonly used in the field. All steps of the pipeline are integrated into RStudio, which reduces learning costs, keeps the flexibility of the analysis process, and facilitates personalized analysis. The pipeline is maintained and updated by the authors and editors of WeChat official account "Meta-genome." Our team will regularly release the latest tutorials both in Chinese and English, read the feedback from users, and provide help to them in the WeChat account and GitHub. The pipeline can be deployed on various platforms, and the installation time is less than half an hour. On an ordinary laptop, the whole analysis process for dozens of samples can be completed within 3 h. The pipeline is available at GitHub (https://github.com/YongxinLiu/EasyAmplicon) and Gitee (https://gitee.com/YongxinLiu/EasyAmplicon).

In the context of anthropogenic global change, the study of landscape effects on species movement has garnered increasing attention. Landscape genetics offer indirect yet attractive means to capture species dispersal events across generations and their interaction with landscapes. However, landscape genetic patterns tend to exhibit significant variations across taxa and rely on the molecular makers adopted. Here, we investigated how landscapes influence population connectivity of an important tea pest, Empoasca onukii , using mitochondrial DNA sequences of 1,518 individuals from 57 locations in mainland China and offshore islands. We analyzed the inter-population genetic divergence and integrated multiple models to explicitly quantify their association with geographic distance, environmental heterogeneity, and landscape barriers. Analyses revealed a reduction in gene flow on islands, along the Yangtze River, and across mountainous regions of Western China. Models explicitly detected the predominant contributions of topographic complexity to population divergence and evidenced that mountains may serve as effective dispersal barriers for E. onukii . These results suggest that the limited gene exchange resulting from low population connectivity among mountains might generate the observed patterns of mitochondrial genetic variations, which contrasts the climate-related pattern previously observed on microsatellites. The findings enhance our comprehension of the evolutionary and epidemic dynamics of E. onukii , and highlight the demand of considering species-specific traits when studying population landscape genetic patterns. Moreover, the study emphasizes the necessity of employing multiple molecular markers to comprehensively elucidate landscape effects on population connectivity across diverse species for valuable insights into biodiversity conservation, pest control, and other management decisions.

The gut microbiomes of arthropods have significant impact on key physiological functions such as nutrition, reproduction, behavior, and health. Spiders are diverse and numerically dominant predators in crop fields where they are potentially important regulators of pests. Harnessing spiders to control agricultural pests is likely to be supported by an understanding of their gut microbiomes, and the environmental drivers shaping microbiome assemblages. This study aimed to deciphering the gut microbiome assembly of these invertebrate predators and elucidating potential implications of key environmental constraints in this process. Here, we used high-throughput sequencing to examine for the first time how the assemblages of bacteria in the gut of spiders are shaped by environmental variables. Local drivers of microbiome composition were globally-relevant input use system (organic production vs. conventional practice), and crop identity (Chinese cabbage vs. cauliflower). Landscape-scale factors, proportion of forest and grassland, compositional diversity, and habitat edge density, also strongly affected gut microbiota. Specific bacterial taxa were enriched in gut of spiders sampled from different settings and seasons. These findings provide a comprehensive insight into composition and plasticity of spider gut microbiota. Understanding the temporal responses of specific microbiota could lead to innovative strategies development for boosting biological control services of predators.

The effect of landscape patterns and environmental factors on the population structure and genetic diversity of organisms is well-documented. However, this effect is still unclear in the case of Mymaridae parasitoids. Despite recent advances in machine learning methods for landscape genetics, ensemble learning still needs further investigation. Here, we evaluated the performance of different boosting algorithms and analyzed the effects of landscape and environmental factors on the genetic variations in the tea green leafhopper parasitoid Stethynium empoasca (Hymenoptera: Mymaridae). The S. empoasca populations showed a distinct pattern of isolation by distance. The minimum temperature of the coldest month, annual precipitation, the coverage of evergreen/deciduous needleleaf trees per 1 km2, and the minimum precipitation of the warmest quarter were identified as the dominant factors affecting the genetic divergence of S. empoasca populations. Notably, compared to previous machine learning studies, our model showed an unprecedented accuracy (r = 0.87) for the prediction of genetic differentiation. These findings not only demonstrated how the landscape shaped S. empoasca genetics but also provided an essential basis for developing conservation strategies for this biocontrol agent. In a broader sense, this study demonstrated the importance and efficiency of ensemble learning in landscape genetics.

ABSTRACTBACKGROUNDUnderstanding the networks of trophic interactions into which generalist predators are embedded is key to assessing their ecological role of in trophic networks and the biological control services they provide. The advent of affordable DNA metabarcoding approaches greatly facilitates quantitative understanding of trophic networks and their response to environmental drivers. Here, we examine how key environmental gradients interact to shape predation by Lycosidae in highly dynamic vegetable growing systems in China.RESULTSFor the sampled Lycosidae, crop identity, pesticide use, and seasons shape the abundance of preydetected in spider guts. For the taxonomic richness of prey, local- and landscape-scale factors gradients were more influential. Multivariate ordinations confirm that these crop-abundant spiders dynamically adjust their diet to reflect environmental constraints and seasonal availability to prey.CONCLUSIONThe plasticity in the diet composition is likely to account for the persistence of spiders in relatively ephemeral brassica crops. Our findings provide further insights into the optimization of habitat management for predator-based biological control practices.

Numerous herbivores orally secrete defense compounds to detoxify plant toxins. However, little is known about the role of orally secreted enzymes by a specialized pest, Plutella xylostella, in the detoxification of plant defense compounds. Three glucosinolate sulfatases (GSSs) or two sulfatase-modifying factors (SUMF1s) mutant strains were established on the basis of CRISPR/Cas9 technology to validate the existence of a species-specific GSSs-SUMF1s system. In comparison to the bioassay data from mutant strains of GSS1/GSS2 or SUMF1a/SUMF1b, GSS3 had a minimal role because no significant change was found in GSS3-/- under different feeding contexts. Antibody-based technologies were used to examine GSSs-related deficient strains, and the results showed that the GSS1 protein was primarily released through larval oral secretion. On the basis of high-performance liquid chromatography, we found that GSS1 was secreted to pre-desulfate the typical plant defensive glucosinolates known as 4-(methylsulfinyl)butyl glucosinolate (4MSOB-GL) to suppress the production of the toxic substance, which is referred to as pre-detoxification strategy. These findings highlighted that the GSSs-SUMF1s system is the key factor for counteradaptation of P. xylostella to cruciferous plants, which strengthens the concept that herbivores deploy pre-detoxification strategies to disrupt the plant chemical defenses to facilitate the colonization process.

The CRISPR/Cas9 system is an efficient tool for reverse genetics validation, and the application of this system in the cell lines provides a new perspective on target gene analysis for the development of biotechnology tools. However, in the cell lines of diamondback moth, Plutella xylostella, the integrity of the CRISPR/Cas9 system and the utilization of this cell lines still need to be improved to ensure the application of the system. Here, we stabilize the transfection efficiency of the P. xylostella cell lines at different passages at about 60% by trying different transfection reagents and adjusting the transfection method. For Cas9 expression in the CRIPSPR/Cas9 system, we identified a strong endogenous promoter: the 217–2 promoter. The dual-luciferase and EGFP reporter assay demonstrated that it has a driving efficiency close to that of the IE1 promoter. We constructed pB-Cas9-Neo plasmid and pU6-sgRNA plasmid for CRISPR/Cas9 system and subsequent cell screening. The feasibility of the CRISPR/Cas9 system in P. xylostella cell lines was verified by knocking out endogenous and exogenous genes. Finally, we generated a transgenic Cas9 cell line of P. xylostella that would benefit future exploitation, such as knock-in and multi-threaded editing. Our works provides the validity of the CRISPR/Cas9 system in the P. xylostella cell lines and lays the foundation for further genetic and molecular studies on insects, particularly favoring gene function analysis.

Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.