Biol Rev Camb Philos Soc , IF:12.82 , 2021 Oct , V96 (5) : P2281-2303 doi: 10.1111/brv.12752
Methodological advances for hypothesis-driven ethnobiology.
Department of Ecology and Evolutionary Biology, University of Tennessee Knoxville, 569 Dabney Hall, Knoxville, TN, 37996, U.S.A.; Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, APK Campus, Auckland Park, Johannesburg, 2006, South Africa.; Faculty of Agronomy, University of Parakou, Parakou, BP 123, Benin.; Department of Botany, University of Hawai'i at Manoa, 3190 Maile Way, 101, Honolulu, HI, 96822, U.S.A.
Ethnobiology as a discipline has evolved increasingly to embrace theory-inspired and hypothesis-driven approaches to study why and how local people choose plants and animals they interact with and use for their livelihood. However, testing complex hypotheses or a network of ethnobiological hypotheses is challenging, particularly for data sets with non-independent observations due to species phylogenetic relatedness or socio-relational links between participants. Further, to account fully for the dynamics of local ecological knowledge, it is important to include the spatially explicit distribution of knowledge, changes in knowledge, and knowledge transmission and use. To promote the use of advanced statistical modelling approaches that address these limitations, we synthesize methodological advances for hypothesis-driven research in ethnobiology while highlighting the need for more figures than tables and more tables than text in ethnobiological literature. We present the ethnobiological motivations for conducting generalized linear mixed-effect modelling, structural equation modelling, phylogenetic generalized least squares, social network analysis, species distribution modelling, and predictive modelling. For each element of the proposed ethnobiologists quantitative toolbox, we present practical applications along with scripts for a widespread implementation. Because these statistical modelling approaches are rarely taught in most ethnobiological programs but are essential for careers in academia or industry, it is critical to promote workshops and short courses focused on these advanced methods. By embracing these quantitative modelling techniques without sacrificing qualitative approaches which provide essential context, ethnobiology will progress further towards an expansive interaction with other disciplines.
PMID: 34056816
Brief Bioinform , IF:11.622 , 2021 Sep , V22 (5) doi: 10.1093/bib/bbab029
Current status and future perspectives of computational studies on human-virus protein-protein interactions.
State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China.; State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
The protein-protein interactions (PPIs) between human and viruses mediate viral infection and host immunity processes. Therefore, the study of human-virus PPIs can help us understand the principles of human-virus relationships and can thus guide the development of highly effective drugs to break the transmission of viral infectious diseases. Recent years have witnessed the rapid accumulation of experimentally identified human-virus PPI data, which provides an unprecedented opportunity for bioinformatics studies revolving around human-virus PPIs. In this article, we provide a comprehensive overview of computational studies on human-virus PPIs, especially focusing on the method development for human-virus PPI predictions. We briefly introduce the experimental detection methods and existing database resources of human-virus PPIs, and then discuss the research progress in the development of computational prediction methods. In particular, we elaborate the machine learning-based prediction methods and highlight the need to embrace state-of-the-art deep-learning algorithms and new feature engineering techniques (e.g. the protein embedding technique derived from natural language processing). To further advance the understanding in this research topic, we also outline the practical applications of the human-virus interactome in fundamental biological discovery and new antiviral therapy development.
PMID: 33693490
Sci Total Environ , IF:7.963 , 2021 Sep , V788 : P147794 doi: 10.1016/j.scitotenv.2021.147794
Destruction of the soil microbial ecological environment caused by the over-utilization of the rice-crayfish co-cropping pattern.
Jiangsu Key Laboratory for Microbes and Functional Genomics, Jiangsu Engineering and Technology Research Centre for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing 210023, China.; Jiangsu Key Laboratory for Microbes and Functional Genomics, Jiangsu Engineering and Technology Research Centre for Industrialization of Microbial Resources, College of Life Sciences, Nanjing Normal University, Nanjing 210023, China. Electronic address: daichuanchao@njnu.edu.cn.
The rice-crayfish co-cropping pattern is a traditional method for the intensive utilization of rice fields. In recent years, this pattern has been over-developed in many countries and regions, especially in China, because of its simple agronomic technology and high economic benefits. However, little is known about the potential ecological problems regarding soil microorganisms caused by the over-utilization of this pattern. The results show that rice-crayfish co-cropping, when over-utilized for a long time, reduced soil microbial richness and diversity compared with rice monocropping. A decrease in bacterial abundance in the nitrogen cycle and an increase in bacterial abundance in the carbon cycle led to a decrease in the nitrogen cycle function and an increase in the carbon cycle function. In an analysis of bacteria that are sensitive to cropping patterns, it was found that in the rice-crayfish co-cropping, the relative abundances of sensitive OTUs from Firmicutes (Bacillus and Clostridium) and Chloroflexi (Anaerolineaceae) were significantly higher during the entire growth period than those observed in the rice monocropping pattern, while the relative abundances of sensitive OTUs from Nitrospirae (Nitrospira), Gemmatimonadetes (Gemmatimonas), and Actinobacteria (Nocardioides) were significantly lower than those observed in the rice monocropping pattern. A network analysis shows that growth-period-sensitive OTUs drive the co-occurrence network modules, although the OTUs also have positive and negative correlations among modules but a positive synergistic effect on the regulation of soil nutrients. In addition, OTUs that were sensitive at the booting stage and filling stage were the key microbial groups in the rice-crayfish co-cropping and rice monocropping networks, respectively. Understanding the classifications and functions of sensitive microbes present during the rice growth period is the basis for formulating a microbial flora management strategy for the rice-crayfish co-cropping pattern, which is of great significance for adjusting agricultural management measures and controlling current soil microbial ecological problems.
PMID: 34029817
mBio , IF:7.867 , 2021 Sep : Pe0101321 doi: 10.1128/mBio.01013-21
Interactions between Viral Regulatory Proteins Ensure an MOI-Independent Probability of Lysogeny during Infection by Bacteriophage P1.
Department of Biochemistry and Biophysics, Texas A&M University, College Station, Texas, USA.; Center for Phage Technology, Texas A&M University, College Station, Texas, USA.; Molecular and Environmental Plant Sciences, Texas A&M University, College Station, Texas, USA.; Department of Computer Science and Engineering, Texas A&M University, College Station, Texas, USA.
Phage P1 is a temperate phage which makes the lytic or lysogenic decision upon infecting bacteria. During the lytic cycle, progeny phages are produced and the cell lyses, and in the lysogenic cycle, P1 DNA exists as a low-copy-number plasmid and replicates autonomously. Previous studies at the bulk level showed that P1 lysogenization was independent of multiplicity of infection (MOI; the number of phages infecting a cell), whereas lysogenization probability of the paradigmatic phage lambda increases with MOI. However, the mechanism underlying the P1 behavior is unclear. In this work, using a fluorescent reporter system, we demonstrated this P1 MOI-independent lysogenic response at the single-cell level. We further observed that the activity of the major repressor of lytic functions (C1) is a determining factor for the final cell fate. Specifically, the repression activity of P1, which arises from a combination of C1, the anti-repressor Coi, and the corepressor Lxc, remains constant for different MOI, which results in the MOI-independent lysogenic response. Additionally, by increasing the distance between phages that infect a single cell, we were able to engineer a lambda-like, MOI-dependent lysogenization upon P1 infection. This suggests that the large separation of coinfecting phages attenuates the effective communication between them, allowing them to make decisions independently of each other. Our work establishes a highly quantitative framework to describe P1 lysogeny establishment. This system plays an important role in disseminating antibiotic resistance by P1-like plasmids and provides an alternative to the lifestyle of phage lambda. IMPORTANCE Phage P1 has been shown potentially to play an important role in disseminating antibiotic resistance among bacteria during lysogenization, as evidenced by the prevalence of P1 phage-like elements in animal and human pathogens. In contrast to phage lambda, a cell fate decision-making paradigm, P1 lysogenization was shown to be independent of MOI. In this work, we built a simple genetic model to elucidate this MOI independency based on the gene-regulatory circuitry of P1. We also proposed that the effective communication between coinfecting phages contributes to the lysis-lysogeny decision-making of P1 and highlighted the significance of spatial organization in the process of cell fate determination in a single-cell environment. Finally, our work provides new insights into different strategies acquired by viruses to interact with their bacterial hosts in different scenarios for their optimal survival.
PMID: 34517752
Plant Cell Physiol , IF:4.927 , 2021 Sep , V62 (4) : P573-581 doi: 10.1093/pcp/pcab010
Environmental Control of Phosphorus Acquisition: A Piece of the Molecular Framework Underlying Nutritional Homeostasis.
Crop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences, Ohwashi 1-1, Tsukuba, Ibaraki, 305-8686 Japan.; Biotechnology Research Center, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo, 113-8657, Japan.
Homeostasis of phosphorus (P), an essential macronutrient, is vital for plant growth under diverse environmental conditions. Although plants acquire P from the soil as inorganic phosphate (Pi), its availability is generally limited. Therefore, plants employ mechanisms involving various Pi transporters that facilitate efficient Pi uptake against a steep concentration gradient across the plant-soil interface. Among the different types of Pi transporters in plants, some members of the PHOSPHATE TRANSPORTER 1 (PHT1) family, present in the plasma membrane of root epidermal cells and root hairs, are chiefly responsible for Pi uptake from the rhizosphere. Therefore, accurate regulation of PHT1 expression is crucial for the maintenance of P homeostasis. Previous investigations positioned the Pi-dependent posttranslational regulation of PHOSPHATE STARVATION RESPONSE 1 (PHR1) transcription factor activity at the center of the regulatory mechanism controlling PHT1 expression and P homeostasis; however, recent studies indicate that several other factors also regulate the expression of PHT1 to modulate P acquisition and sustain P homeostasis against environmental fluctuations. Together with PHR1, several transcription factors that mediate the availability of other nutrients (such as nitrogen and zinc), light, and stress signals form an intricate transcriptional network to maintain P homeostasis under highly diverse environments. In this review, we summarize this intricate transcriptional network for the maintenance of P homeostasis under different environmental conditions, with a main focus on the mechanisms identified in Arabidopsis.
PMID: 33508134
DNA Res , IF:4.458 , 2021 Sep , V28 (5) doi: 10.1093/dnares/dsab018
Chromosome-level genome assembly of Gynostemma pentaphyllum provides insights into gypenoside biosynthesis.
College of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530200, China.; Guangxi Key Laboratory of Zhuang and Yao Ethnic Medicine, Guangxi University of Chinese Medicine, Nanning 530200, China.; Guangdong Provincial Key Laboratory of Crops Genetics & Improvement, Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China.
Gynostemma pentaphyllum (Thunb.) Makino is an economically valuable medicinal plant belonging to the Cucurbitaceae family that produces the bioactive compound gypenoside. Despite several transcriptomes having been generated for G. pentaphyllum, a reference genome is still unavailable, which has limited the understanding of the gypenoside biosynthesis and regulatory mechanism. Here, we report a high-quality G. pentaphyllum genome with a total length of 582 Mb comprising 1,232 contigs and a scaffold N50 of 50.78 Mb. The G. pentaphyllum genome comprised 59.14% repetitive sequences and 25,285 protein-coding genes. Comparative genome analysis revealed that G. pentaphyllum was related to Siraitia grosvenorii, with an estimated divergence time dating to the Paleogene ( approximately 48 million years ago). By combining transcriptome data from seven tissues, we reconstructed the gypenoside biosynthetic pathway and potential regulatory network using tissue-specific gene co-expression network analysis. Four UDP-glucuronosyltransferases (UGTs), belonging to the UGT85 subfamily and forming a gene cluster, were involved in catalyzing glycosylation in leaf-specific gypenoside biosynthesis. Furthermore, candidate biosynthetic genes and transcription factors involved in the gypenoside regulatory network were identified. The genetic information obtained in this study provides insights into gypenoside biosynthesis and lays the foundation for further exploration of the gypenoside regulatory mechanism.
PMID: 34499150
BMC Plant Biol , IF:4.215 , 2021 Sep , V21 (1) : P427 doi: 10.1186/s12870-021-03206-z
Genome-wide identification and analysis of WRKY gene family in maize provide insights into regulatory network in response to abiotic stresses.
Anhui Provincial Key Lab. of the Conservation and Exploitation of Biological Resources, Anhui Normal University, Wuhu, 241000, China.; Anhui Provincial Key Lab. of the Conservation and Exploitation of Biological Resources, Anhui Normal University, Wuhu, 241000, China. qyx2011@ahnu.edu.cn.
BACKGROUND: The WRKY transcription factor family plays significant roles in biotic and abiotic stress responses, which has been associated with various biological processes in higher plants. However, very little is known regarding the structure and function of WRKY genes in maize. RESULTS: In this study, a total of 140 ZmWRKY proteins encoded by 125 ZmWRKY genes were eventually identified in maize. On the basis of features of molecular structure and a comparison of phylogenetic relationships of WRKY transcription factor families from Arabidopsis, rice and maize, all 140 ZmWRKY proteins in maize were divided into three main groups (Groups I, II and III) and the Group II was further classified into five subgroups. The characteristics of exon-intron structure of these putative ZmWRKY genes and conserved protein motifs of their encoded ZmWRKY proteins were also presented respectively, which was in accordance with the group classification results. Promoter analysis suggested that ZmWRKY genes shared many abiotic stress-related elements and hormone-related elements. Gene duplication analysis revealed that the segmental duplication and purifying selection might play a significant role during the evolution of the WRKY gene family in maize. Using RNA-seq data, transcriptome analysis indicated that most of ZmWRKY genes displayed differential expression patterns at different developmental stages of maize. Further, by quantitative real-time PCR analysis, twenty-one ZmWRKY genes were confirmed to respond to two different abiotic stress treatments, suggesting their potential roles in various abiotic stress responses. In addition, RNA-seq dataset was used to conduct weighted gene co-expression network analysis (WGCNA) in order to recognize gene subsets possessing similar expression patterns and highly correlated with each other within different metabolic networks. Further, subcellular localization prediction, functional annotation and interaction analysis of ZmWRKY proteins were also performed to predict their interactions and associations involved in potential regulatory network. CONCLUSIONS: Taken together, the present study will serve to present an important theoretical basis for further exploring function and regulatory mechanism of ZmWRKY genes in the growth, development, and adaptation to abiotic stresses in maize.
PMID: 34544366