Genome-Wide Analysis of Aux/IAA Gene Family in Artemisia argyi: Identification, Phylogenetic Analysis, and Determination of Response to Various Phytohormones

Artemisia argyi is a traditional herbal medicine plant, and its folium artemisia argyi is widely in demand due to moxibustion applications globally. The Auxin/indole-3-acetic acid (Aux/IAA, or IAA) gene family has critical roles in the primary auxin-response process, with extensive involvement in plant development and stresses, controlling various essential traits of plants. However, the systematic investigation of the Aux/IAA gene family in A. argyi remains limited. In this study, a total of 61 Aux/IAA genes were comprehensively identified and characterized. Gene structural analysis indicated that 46 Aux/IAA proteins contain the four typical domains, and 15 Aux/IAA proteins belong to non-canonical IAA proteins. Collinear prediction and phylogenetic relationship analyses suggested that Aux/IAA proteins were grouped into 13 distinct categories, and most Aux/IAA genes might experience gene loss during the tandem duplication process. Promoter cis-element investigation indicated that Aux/IAA promoters contain a variety of plant hormone response and stress response cis-elements. Protein interaction prediction analysis demonstrated that AaIAA26/29/7/34 proteins are possibly core members of the Aux/IAA family interaction. Expression analysis in roots and leaves via RNA-seq data indicated that the expression of some AaIAAs exhibited tissue-specific expression patterns, and some AaIAAs were involved in the regulation of salt and saline-alkali stresses. In addition, RT-qPCR results indicated that AaIAA genes have differential responses to auxin, with complex response patterns in response to other hormones, indicating that Aux/IAA may play a role in connecting auxin and other hormone signaling pathways. Overall, these findings shed more light on AaIAA genes and offer critical foundational knowledge toward the elucidation of their function during plant growth, stress response, and hormone networking of Aux/IAA family genes in A. argyi.

Floral Volatile Organic Compounds Change the Composition and Function of the Endophytic Fungal Community in the Flowers of Osmanthus fragrans

Endophytic fungi in flowers influence plant health and reproduction. However, whether floral volatile organic compounds (VOCs) affect the composition and function of the endophytic fungal community remains unclear. Here, gas chromatography-mass spectrometry (GC-MS) and high-throughput sequencing were used to explore the relationship between floral VOCs and the endophytic fungal community during different flower development stages in Osmanthus fragrans 'Rixiang Gui'. The results showed that the composition of the endophytic fungal community and floral VOCs shifted along with flowering development. The highest and lowest α diversity of the endophytic fungal community occurred in the flower fading stage and full blooming stage, respectively. The dominant fungi, including Dothideomycetes (class), Pleosporales (order), and Neocladophialophora, Alternaria, and Setophoma (genera), were enriched in the flower fading stage and decreased in the full blooming stage, demonstrating the enrichment of the Pathotroph, Saprotroph, and Pathotroph-Saprotroph functions in the flower fading stage and their depletion in the full blooming stage. However, the total VOC and terpene contents were highest in the full blooming stage and lowest in the flower fading stage, which was opposite to the α diversity of the endophytic fungal community and the dominant fungi during flowering development. Linalool, dihydro-β-ionone, and trans-linalool oxide(furan) were key factors affecting the endophytic fungal community composition. Furthermore, dihydro-β-ionone played an extremely important role in inhibiting endophytic fungi in the full blooming stage. Based on the above results, it is believed that VOCs, especially terpenes, changed the endophytic fungal community composition in the flowers of O. fragrans 'Rixiang Gui'. These findings improve the understanding of the interaction between endophytic fungi and VOCs in flowers and provide new insight into the mechanism of flower development.

[Changes in the structure and function of soil prokaryotic communities in subalpine Picea asperata plantations]

The structural and functional characteristics of soil prokaryotic community are important for maintaining ecosystem functions. In this study, we examined the diversity and compositions, the key drivers, as well as functional characteristics of prokaryotic communities in the rhizosphere and non-rhizosphere soils of Picea asperata with different stand ages using high-throughput sequencing technique and bioinformatics methods. The results showed that β-diversity of soil prokaryotic communities in both rhizosphere and non-rhizosphere showed significant differences among different stand ages, but no significant difference between rhizosphere and non-rhizosphere in the same stand age. In terms of community composition at the phylum level, the relative abundances of Proteobacteria and Rokubacteria showed an increasing trend with the increases of stand age, while the relative abundance of Actinobacteria showed a decreasing trend, but no significant difference was observed between 75 year-old planted forests (PF75) and natural forests (NF). The relative abundances of Firmicutes and Thaumarchaeota in the soil of the 25 year-old planted forests (PF25) were significantly higher than in other planted forests and NF. At the genus level, the relative abundances of RB41, Terrimonas and Acidibacter showed an increasing trend with the increases of stand age, and RB41 and Terrimonas in rhizosphere soil of PF75 were significantly higher than those in NF. Soil properties and vegetation characteristics jointly influenced the structure of soil prokaryotic communities, with herb layer coverage, soil pH, total phosphorus, and total nitrogen as major drivers. The functional characteristics of soil prokaryotic communities were significantly different among different stand ages. The relative abundances of functions involved in carbon and nitrogen cycle, e.g., cellulolysis and nitrification, decreased with the increases of stand age, whereas that of sulfate respiration involved in the sulfur cycle increased. We proposed that the structure and functional characteristics of soil prokaryotic communities could serve as important indicators of the development stages of P. asperata forests. In the later stages of plantation forest development, soil nutrient availability could be improved by mediating phosphorus-dissolving and nitrogen-enhancing microorganisms to maintain the stability of the plantation ecosystem.

Identification, biogenesis, and function prediction of a novel circRNA_3238 of chicken

With the development of high-throughput sequencing, circular RNA has come into people's vision and attracted more and more attention. Many studies have found that circular RNA plays an important role in a variety of biological processes and the occurrence and development of diseases. According to the previous sequencing results, circRNA_3238 was differentially expressed in ALV-J infected group and the non-infected group was selected for subsequent verification and analysis. We found that circRNA_3238 is a stable, circular transcript, which mainly exists in the cytoplasm. And it is widely expressed in various tissues of chickens, and highly expressed in lung, lymph, and bursa of fabricius. Bioinformatics results show that circRNA_3238 and the predicted target genes enriched MAPK signaling pathway, Notch signaling pathway, and other pathways related to disease or immune, revealing circRNA_3238 may indirectly regulate the process of ALV-J infection by regulating target genes.

Potential functions of the shared bacterial taxa in the citrus leaf midribs determine the symptoms of Huanglongbing

Instruction

Citrus is a globally important fruit tree whose microbiome plays a vital role in its growth, adaptability, and resistance to stress.

Methods

With the high throughput sequencing of 16S rRNA genes, this study focused on analyzing the bacterial community, especially in the leaf midribs, of healthy and Huanglongbing (HLB)-infected plants.

Results

We firstly identified the shared bacterial taxa in the midribs of both healthy and HLB-infected plants, and then analyzed their functions. Results showed that the shared bacterial taxa in midribs belonged to 62 genera, with approximately 1/3 of which modified in the infected samples. Furthermore, 366 metabolic pathways, 5851 proteins, and 1833 enzymes in the shared taxa were predicted. Among these, three metabolic pathways and one protein showed significant importance in HLB infection. With the random forest method, six genera were identified to be significantly important for HLB infection. Notably, four of these genera were also among the significantly different shared taxa. Further functional characterization of these four genera revealed that Pseudomonas and Erwinia likely contributed to plant defense against HLB, while Streptomyces might have implications for plant defense against HLB or the pathogenicity of Candidatus Liberibacter asiaticus (CLas).

Disccusion

Overall, our study highlights that the functions of the shared taxa in leaf midribs are distinguished between healthy and HLB-infected plants, and these microbiome-based findings can contribute to the management and protection of citrus crops against CLas.

[Effects of Vegetation Types and Seasonal Dynamics on the Diversity and Function of Soil Bacterial Communities in the Upper Reaches of the Heihe River]

The process of interaction between the plant and soil microbial communities holds the key to understanding the biogeochemical cycle and preserving the stability of vegetation ecosystems. Owing to this significance, the primary goal of this research was to give a starting point and reference methods to restore local vegetation. The vegetation distribution in the mountainous area of the upper reaches of the Heihe River Basin had notable vertical zonality, which was characterized by five typical vegetation types, including cushion vegetation(CV), herbage meadow(HM), forest steppe(FS), mountainous steppe(MS), and desert grassland(DG). The organization and diversity of soil bacterial communities in various vegetation types were examined using high-throughput sequencing techniques in both the winter and summer seasons. Sampling sites were chosen in each of the five common vegetation types in turn. Additionally, based on the FAPROTAX database, the predicted functions of microbial communities were evaluated for different vegetation types and seasons. The redundancy analysis and structural equation model were also used to investigate the primary environmental elements and uncover the mechanisms affecting the soil bacterial populations. The findings revealed that:① the physical and chemical properties of soil differed significantly among vegetation types and seasons, and the property indices varied dissimilarly with depth. In particular, the soil water content(SWC) and nutrient content of total organic carbon(TOC) and total nitrogen(TN) were significantly higher in forest grassland(FS). ② The divergences of α-diversity indices among seasons(P<0.05) were greater than that of vegetation types(P>0.05). The Chao1 index measuring the abundance of the bacterial community was higher in winter. According to the Shannon index, the species of the bacterial community were dispersed in a "W" shape in the summer and a "hump" form in the winter with altitude. ③ The predominant phyla of the bacterial community, composed of Acidobacteria, Proteobacteria, and Actinobacteria, did not significantly differ from one another. However, the organization of the bacterial community presented a significant variation seasonally at the genus level. ④ The primary functions of the soil bacterial population, which largely consisted of chemoheterotrophy, nitrification, and aerobic ammonia oxidation, were not significantly different among vegetation types and seasons. ⑤ The key factors affecting soil bacterial communities at the genus level varied significantly among seasons, with soil temperature(ST), total organic carbon(TOC), and pH in winter and soil water content(SWC), carbon-nitrogen ratio(C/N), and pH in summer. ⑥ Synergized by interrelated environmental factors, soil physical and chemical features exerted a more direct impact on the diversity and functionality of bacterial communities compared with vegetation types, including significantly changing the abundance of Acidobacteria and Bacteroidetes, as well as the role of nitrification and ammonia oxidation. Hence, improving the carbon and nitrogen contents in soil nutrients would help to enhance the diversity and function of bacterial communities. The findings of this study provided a model for determining the mechanism of regional vegetation degradation and preserving the stability of alpine ecosystems in this area by revealing the seasonal distribution pattern of bacterial communities and the key biological processes beneath the typical vertical vegetation band in the upper reaches of the Heihe River.

iORbase: A database for the prediction of the structures and functions of insect olfactory receptors

Insect olfactory receptors (iORs) with atypical 7-transmembrane domains, unlike Chordata olfactory receptors, are not in the GPCR protein family. iORs selectively bind to volatile ligands in the environment and affect essential insect behaviors. In this study, we constructed a new platform (iORbase, https://www.iorbase.com) for the structural and functional analysis of iORs based on a combined algorithm for gene annotation and protein structure prediction. Moreover, it provides the option to calculate the binding affinities and binding residues between iORs and pheromone molecules by virtual screening of docking. Furthermore, iORbase supports the automatic structural and functional prediction of user-submitted iORs or pheromones. iORbase contains the well-analyzed results of approximately 6 000 iORs and their 3D protein structures identified from 59 insect species and 2 077 insect pheromones from the literature, as well as approximately 12 million pairs of simulated interactions between functional iORs and pheromones. We also built 4 online modules, iORPDB, iInteraction, iModelTM, and iOdorTool to easily retrieve and visualize the 3D structures and interactions. iORbase can help greatly improve the experimental efficiency and success rate, identify new insecticide targets, or develop electronic nose technology. This study will shed light on the olfactory recognition mechanism and evolutionary characteristics from the perspectives of omics and macroevolution.

Current successes and remaining challenges in protein function prediction

In recent years, improvements in protein function prediction methods have led to increased success in annotating protein sequences. However, the functions of over 30% of protein-coding genes remain unknown for many sequenced genomes. Protein functions vary widely, from catalyzing chemical reactions to binding DNA or RNA or forming structures in the cell, and some types of functions are challenging to predict due to the physical features associated with those functions. Other complications in understanding protein functions arise due to the fact that many proteins have more than one function or very small differences in sequence or structure that correspond to different functions. We will discuss some of the recent developments in predicting protein functions and some of the remaining challenges.

[Effects of Biogas Slurry Application on Soil Microbial Communities Structure and Function During Wheat-rice Stubble Period]

To reveal the effects of biogas slurry application on soil microbial community structure and function, a soil column experiment was constructed with three treatments[(no N addition, CM; conventional fertilization, SN; biogas slurry addition, SZ)]. The differences in composition, diversity, and structure of bacterial and fungal communities on day 1 and day 21 after soil flooding were evaluated, and their functions were predicted using Illumina high-throughput sequencing technology. The results of the analysis of α diversity showed that the fungal α-diversity indexes of CM, SN, and SZ treatments on day 1 were significantly higher than those on day 21, and there was no significant difference among the three treatments. However, the bacterial Simpson index differed among the three treatments on day 21, with SZ-21 showing a higher Simpson index but lower Chao1 index compared with those of SZ-21. The analysis of bacterial community structure showed that Firmicutes, Chloroflexi, and Actinobacteria in the SN-1 treatment were different from those in the other treatments on day 1, whereas the relative abundance of bacterial phyla in the SZ and SN treatments were similar on day 21. The analysis of fungal community structure showed that the relative abundance of Ascomycota and Zygomycota in the SZ-1 treatment were higher than those in the SN-1 and CM-1 treatments on day 1. The relative abundance of Ascomycota in the SN-21 and SZ-21 treatments were lower, whereas that of Zygomycota were higher compared with that in CM-21. The analysis of NMDS showed that the composition of bacterial and fungal communities in the SN and SZ treatments showed a gradually similar trend. The PICRUSt analysis showed that the function of the soil bacterial community was similar in the CM, SN, and SZ treatments. The FUNGuild function prediction reflected that the main differences in trophic type between the SN-21 and SZ-21 treatments occurred in saprotroph and pathotroph forms. Therefore, biogas slurry addition in the wheat-rice stubble stage could contribute to balancing soil nutrients and maintaining soil ecological function to a certain extent, but there may still be a risk of fungal disease.

Gut microbial diversity and function analysis of the final-instar larvae of Protohermes xanthodes (Megaloptera: Corydalidae)

Protohermes xanthodes (Megaloptera, Corydalidae, Protohermes), widespread species in China, is an important insects treated as food and medicine for aquaculture. In this study, the gut microbiota was investigated by 16S rRNA microbial profiling. A total of 600 Amplicon Sequence Variants (ASV) were identified, Proteobacteria and Firmicutes were the main dominant phyla, and 27 genera ran through the entire digestive tract, mainly Hafnia-Obesumbacterium (Proteobacteria), Lactobacillus and Lactococcus (Firmicutes). The PICRUSt2 functional prediction of gut microbiota showed that the foregut abundant pathways related to metabolism, environmental information processing, and genetic information processing. while the midgut had the most abundant metabolic and environmental information processing pathways, including the prominent phosphotransferase system (PTS), propionate metabolism, and β-lactam resistance. The hindgut had the weakest metabolic function, but its genetic information processing was more abundant than the foregut and midgut. Additionally, 26 strains of bacteria were isolated from the midgut microorganisms, with Firmicutes being the dominant bacteria, and some of the purified bacteria had potential probiotic and anti-pathogen functions. These findings suggest that there are differences in the microorganisms of the different gut floras of the larvae, and each flora has specific metabolic functions. This research could be used to further understand the function of gut microorganisms, explore the co-evolution of P. xanthodes and gut microorganisms, and promote healthy breeding based on gut microorganisms.

[Advances in machine learning for predicting protein functions]

Proteins play a variety of functional roles in cellular activities and are indispensable for life. Understanding the functions of proteins is crucial in many fields such as medicine and drug development. In addition, the application of enzymes in green synthesis has been of great interest, but the high cost of obtaining specific functional enzymes as well as the variety of enzyme types and functions hamper their application. At present, the specific functions of proteins are mainly determined through tedious and time-consuming experimental characterization. With the rapid development of bioinformatics and sequencing technologies, the number of protein sequences that have been sequenced is much larger than those can be annotated, thus developing efficient methods for predicting protein functions becomes crucial. With the rapid development of computer technology, data-driven machine learning methods have become a promising solution to these challenges. This review provides an overview of protein function and its annotation methods as well as the development history and operation process of machine learning. In combination with the application of machine learning in the field of enzyme function prediction, we present an outlook on the future direction of efficient artificial intelligence-assisted protein function research.

High-Accuracy ncRNA Function Prediction via Deep Learning Using Global and Local Sequence Information

The prediction of the biological function of non-coding ribonucleic acid (ncRNA) is an important step towards understanding the regulatory mechanisms underlying many diseases. Since non-coding RNAs are present in great abundance in human cells and are functionally diverse, developing functional prediction tools is necessary. With recent advances in non-coding RNA biology and the availability of complete genome sequences for a large number of species, we now have a window of opportunity for studying non-coding RNA biology. However, the computational methods used to predict the non-coding RNA functions are mostly either scarcely accurate, when based on sequence information alone, or prohibitively expensive in terms of computational burden when a secondary structure prediction is needed. We propose a novel computational method to predict the biological function of non-coding RNA genes that is based on a collection of deep network architectures utilizing solely ncRNA sequence information and which does not rely on or require expensive secondary ncRNA structure information. The approach presented in this work exhibits comparable or superior accuracy to methods that employ both sequence and structural features, at a much lower computational cost.

Effects of different botanical oil meal mixed with cow manure organic fertilizers on soil microbial community and function and tobacco yield and quality

Introduction

The continuous application of cow manure in soil for many years leads to the accumulation of heavy metals, pathogenic microorganisms, and antibiotic resistance genes. Therefore, in recent years, cow manure has often been mixed with botanical oil meal as organic fertilizer applied to farmland to improve soil and crop quality. However, the effects of various botanical oil meal and cow manure mixed organic fertilizers on soil microbial composition, community structure, and function, tobacco yield, and quality remain unclear.

Methods

Therefore, we prepared organic manure via solid fermentation by mixing cow manure with different oil meals (soybean meal, rape meal, peanut bran, sesame meal). Then, we studied its effects on soil microbial community structure and function, physicochemical properties, enzyme activities, tobacco yield and quality; then we analyzed the correlations between these factors.

Results and discussion

Compared with cow manure alone, the four kinds of mixed botanical oil meal and cow manure improved the yield and quality of flue-cured tobacco to different degrees. Peanut bran, which significantly improved the soil available phosphorus, available potassium, and NO₃^--N, was the best addition. Compared with cow manure alone, soil fungal diversity was significantly decreased when rape meal or peanut bran was combined with cow manure, while soil bacterial and fungal abundance was significantly increased when rape meal was added compared with soybean meal or peanut bran. The addition of different botanical oil meals significantly enriched the subgroup_7 and Spingomonas bacteria and Chaetomium and Penicillium fungi in the soil. The relative abundances of functional genes of xenobiotics biodegradation and metabolism, soil endophytic fungi, and wood saprotroph functional groups increased. In addition, alkaline phosphatase had the greatest effect on soil microorganisms, while NO₃^--N had the least effect on soil microorganisms. In conclusion, the mixed application of cow manure and botanical oil meal increased the available phosphorus and potassium contents in soil; enriched beneficial microorganisms; promoted the metabolic function of soil microorganisms; increased the yield and quality of tobacco; and improved the soil microecology.

[Effects of Chinese Milk Vetch Returning Incorporated with Chemical Fertilizer Reduction on the Composition and Function of Soil Bacterial Communities in Paddy Fields]

Chinese milk vetch (Astragalus sinicus L.) is an important organic nutrient resource in the southern Henan rice-growing area. Thus, the effects of Chinese milk vetch (MV) returning incorporated with reduced chemical fertilizer on the physicochemical properties and bacterial community characteristics in paddy soil were studied. These results can provide a certain theoretical basis for the improvement of soil fertility and reduction of chemical fertilizer in this area. A field experiment was conducted for 12 consecutive years, involving six fertilization treatments (blank control, CK; 100% chemical fertilizer, F100; 80% chemical fertilizer+22.5 t·hm^-2 MV, MV1F80; 80% chemical fertilizer+45 t·hm^-2 MV, MV2F80; 60% chemical fertilizer+22.5 t·hm^-2 MV, MV1F60; and 60% chemical fertilizer+45 t·hm^-2 MV, MV2F60). The high-throughput sequencing method was used to compare the effects of different fertilization treatments on soil bacterial community diversity, composition, and structural characteristics. The FAPROTAX function prediction method was used to analyze the abundance differences of functional groups between different fertilization treatments. Additionally, combined with soil physicochemical properties and bacterial community characteristics, we explored the key soil environmental factors that changed the structure and functional characteristics of the soil bacterial community. Compared with that under CK, the soil bulk density (BD) under the MV returning incorporated with reduced chemical fertilizer treatment was decreased, whereas soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK) were increased by 12.7%-35.5%, 38.2%-65.7%, 66.7%-95.2%, and 20.3%-31.6%, respectively. Compared with that under the F100 treatment, the Sobs index and Shannon diversity index of the bacterial community under the MV returning incorporated with reduced chemical fertilizer were decreased, and the Sobs index and Shannon diversity index were significantly positively correlated with BD (P<0.05) but significantly negatively correlated with SOC and TN (P<0.05). Compared with that under the F100 treatment, the relative abundances of Firmicutes under the MV1F80 and MV2F60 treatments were significantly increased by 82.2% and 67.4% (P<0.05), but the relative abundances of Acidobacteria were significantly reduced by 32.6% and 40.5% (P<0.05), respectively. The relative abundance of Actinobacteria under the MV2F60 treatment was significantly increased by 30.0% (P<0.05) compared with that under the F100 treatment. According to RDA analysis, soil SOC, TN, and TK were the main soil environmental factors that significantly affected bacterial community (P<0.05). Compared with that under CK and the F100 treatment, the abundance of functional groups of chemoheterotrophy, nitrogen fixation, fermentation, and ureolysis under the MV returning incorporated with reduced chemical fertilizer treatment were improved, whereas the abundance of functional groups of animal parasites or symbionts, all human pathogens, and human pathogen pneumonia were reduced, particularly under MV1F80 and MV2F60. To summarize, the long-term MV returning to the field incorporated with reduced chemical fertilizer improved the soil physical and chemical properties, thus changing the structure and functional characteristics of the soil bacterial communities, contributing to the improvement in the soil fertility, stability, and health of micro-ecosystems in paddy fields, thus ensuring the green and sustainable development of regional agriculture.

Study on the effect of additives on microbial diversity, predicted functional profiles, and fermentation quality of Broussonetia papyrifera and Pennisetum sinese mixed ensilage in the karst region

In this research we evaluated the effect of exogenous lactic acid bacteria (LAB) and Amomum villosum essential oil (AVEO) on the chemical composition, microbial community composition, microbial functional diversity, and fermentation quality of Broussonetia papyrifera (BP) and Pennisetum sinese (PS) mixed silages. The BP: PS mixing ratios were 100:0, 70:30, 50:50, 30:70, and 0:100. After 3 and 30 days of ensiling at 22-25°C, microbial diversity and function, and fermentation quality, was assessed. Increasing PS content resulted in decreased ammoniacal nitrogen and pH, increased water-soluble carbohydrate content, increased relative abundance of Lactococcus and Acinetobacter, and reduced relative abundance of Caproiciproducens and Pseudomonas. A 50:50 BP: PS ratio effectively improved the fermentation quality compared to anaerobic fermentation with BP or PS alone, while AVEO treatment further improved fermentation quality by increasing Lactococcus relative abundance. Moreover, as fermentation proceeded, ensiling enhanced the "Human diseases", "Environmental information processing", and "Cellular processes" functions at the first level, as well as the "Two-component system" and "ABC transporters" functions at the third level. Different additives affected the fermentation of BP and PS mixed silage by regulating microbial community succession and metabolic pathways during ensiling.

Comparative Analyses of the Fecal Microbiome of Five Wild Black-Billed Capercaillie (Tetrao parvirostris) Flocks

Black-billed capercaillie (Tetrao parvirostris) was listed as a first-class state-protected animal because it was endangered in China (Category I). This study is the first to examine the diversity and composition of T. parvirostris gut microbiome in the wild. We collected fecal samples from five black-billed capercaillie flock roosting sites (each 20 km apart) in one day. Thirty fecal samples were sequenced with 16S rRNA gene amplicons on the Illumina HiSeq platform. This study is the first to analyze the fecal microbiome composition and diversity of black-billed capercaillie in the wild. At the phylum level, Camplyobacterota, Bacillota, Cyanobacteria, Actinomycetota, and Bacteroidota were the most abundant in the fecal microbiome of black-billed capercaillie. At the genus level, unidentified Chloroplast, Escherichia-Shigella, Faecalitalea, Bifidobacterium, and Halomonas were the dominant genera. Based on alpha and beta diversity analyses, we found no significant differences in the fecal microbiome between five flocks of black-billed capercaillie. Protein families: genetic information processing; protein families: signaling and cellular processes, carbohydrate metabolism; protein families: metabolism and energy metabolism are the main predicted functions of the black-billed capercaillie gut microbiome through the PICRUSt2 method. This study reveals the composition and structure of the fecal microbiome of the black-billed capercaillie under wild survival conditions, and this study provides scientific data for the comprehensive conservation of the black-billed capercaillie.

Using evolutionary data to make sense of macromolecules with a "face-lifted" ConSurf

The ConSurf web-sever for the analysis of proteins, RNA, and DNA provides a quick and accurate estimate of the per-site evolutionary rate among homologues. The analysis reveals functionally important regions, such as catalytic and ligand-binding sites, which often evolve slowly. Since the last report in 2016, ConSurf has been improved in multiple ways. It now has a user-friendly interface that makes it easier to perform the analysis and to visualize the results. Evolutionary rates are calculated based on a set of homologous sequences, collected using hidden Markov model-based search tools, recently embedded in the pipeline. Using these, and following the removal of redundancy, ConSurf assembles a representative set of effective homologues for protein and nucleic acid queries to enable informative analysis of the evolutionary patterns. The analysis is particularly insightful when the evolutionary rates are mapped on the macromolecule structure. In this respect, the availability of AlphaFold model structures of essentially all UniProt proteins makes ConSurf particularly relevant to the research community. The UniProt ID of a query protein with an available AlphaFold model can now be used to start a calculation. Another important improvement is the Python re-implementation of the entire computational pipeline, making it easier to maintain. This Python pipeline is now available for download as a standalone version. We demonstrate some of ConSurf's key capabilities by the analysis of caveolin-1, the main protein of membrane invaginations called caveolae.

Bacterial Community Composition and Function of Tropical River Ecosystem along the Nandu River on Hainan Island, China

Microorganisms play a pivotal role in nutrient cycling in aquatic ecosystems. Understanding bacterial diversity and its functional composition are crucial for aquatic ecology and protection. We investigated the bacterial community structure using 16S rRNA gene amplicons high-throughput sequencing in this study. Results showed that 105 amplicon sequence variants (ASVs) account for 43.8% of the total sequences shared by the Nandu River's lower, middle, and upper reach and the Songtao Reservoir. The dominant bacterial phylum in the Nandu River and its connected Songtao Reservoir were Proteobacteria and Actinobacteriota, respectively. The highest Chao1 and Shannon index values were found in the lower reach of the Nandu River. Beta diversity analysis showed the divergence in bacterial communities in the Nandu River and Songtao Reservoir, but not in different reaches. Among the water properties, based on the Mantel test, dissolved oxygen, total nitrogen, and nitrite significantly affected the bacterial communities. The functional profiles predicted by Tax4Fun2 showed that metabolism was the most abundant function group. The relative abundance of genetic information processing was significantly higher in the Songtao Reservoir than in the Nandu River, while the relative abundance of human diseases was significantly lower in the Songtao Reservoir than in the Nandu River. The appearance of the xenobiotics biodegradation and metabolism function group requires us to pay more attention to possible water pollution, especially at the upper reach of the Nandu River.

Function Prediction of Peptide Toxins with Sequence-Based Multi-Tasking PU Learning Method

Peptide toxins generally have extreme pharmacological activities and provide a rich source for the discovery of drug leads. However, determining the optimal activity of a new peptide can be a long and expensive process. In this study, peptide toxins were retrieved from Uniprot; three positive-unlabeled (PU) learning schemes, adaptive basis classifier, two-step method, and PU bagging were adopted to develop models for predicting the biological function of new peptide toxins. All three schemes were embedded with 14 machine learning classifiers. The prediction results of the adaptive base classifier and the two-step method were highly consistent. The models with top comprehensive performances were further optimized by feature selection and hyperparameter tuning, and the models were validated by making predictions for 61 three-finger toxins or the external HemoPI dataset. Biological functions that can be identified by these models include cardiotoxicity, vasoactivity, lipid binding, hemolysis, neurotoxicity, postsynaptic neurotoxicity, hypotension, and cytolysis, with relatively weak predictions for hemostasis and presynaptic neurotoxicity. These models are discovery-prediction tools for active peptide toxins and are expected to accelerate the development of peptide toxins as drugs.

Succession of the microbial communities and metabolic functions in composting or deep burial processing of dead chickens

1. This study examined the effects of composting and deep burial techniques on degradation efficiency of dead chickens. Different raw materials (crushed branches or rape straws) and disinfectants (quicklime or bleaching powder) were applied in composting and deep burial process, respectively. The whole process lasted for 90 d in both summer and winter.2. High throughput sequencing displayed that Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria and Deinococcus-Thermus were the most dominant bacterial phyla during the experiment. The relative abundance of Firmicutes dwindled gradually with prolonged composting duration, while Proteobacteria, Bacteroidetes and Deinococcus-Thermous increased gradually over time.3. The bacterial functions identified from the KEGG pathway showed that amino acid and carbohydrate metabolism were the major microbial metabolic pathways that determined final degradation efficiency. At the end of the trial, the decomposition status of chicken carcasses and faecal coliforms were measured.4. The results demonstrated that the optimum decomposition effect was obtained in composting compared with other treatment groups. Low ambient temperature reduced degradation efficiency, due to restricted microbial activity. In addition, faecal coliforms were not completely removed by the deep burial process of dead chickens in winter.5.These findings provide a theoretical basis for the feasibility of composting chicken carcasses instead of deep burial.

Keystone Taxa and Predictive Functional Analysis of Sphagnum palustre Tank Microbiomes in Erxianyan Peatland, Central China

Sphagnum is a fundamental ecosystem of engineers, including more than 300 species around the world. These species host diverse microbes, either endosymbiotic or ectosymbiotic, and are key to carbon sequestration in peatland ecosystems. However, the linkages between different types of Sphagnum and the diversity and ecological functions of Sphagnum-associated microbiomes are poorly known, and so are their joint responses to ecological functions. Here, we systematically investigated endophytes in Sphagnum palustre via next-generation sequencing (NGS) techniques in the Erxianyan peatland, central China. The total bacterial microbiome was classified into 38 phyla and 55 classes, 122 orders and 490 genera. The top 8 phyla of Proteobacteria (33.69%), Firmicutes (11.94%), Bacteroidetes (9.42%), Actinobacteria (6.53%), Planctomycetes (6.37%), Gemmatimonadetes (3.05%), Acidobacteria (5.59%) and Cyanobacteria (1.71%) occupied 78.31% of total OTUs. The core microbiome of S. palustre was mainly distributed mainly in 7 phyla, 9 classes, 15 orders, 22 families and 43 known genera. There were many differences in core microbiomes compared to those in the common higher plants. We further demonstrate that the abundant functional groups have a substantial potential for nitrogen fixation, carbon cycle, nitrate metabolism, sulfate respiration and chitinolysis. These results indicate that potential ecological function of Sphagnum palustre in peatlands is partially rooted in its microbiomes, and that incorporating into functional groups of Sphagnum-associated microbiomes can promote mechanistic understanding of Sphagnum ecology in subalpine peatlands.

[Microbial Community Structure of Activated Sludge for Total Nitrogen Upgrading Project]

The activated sludge of a biochemical unit (WLK_OD) and an advanced denitrification unit (WLK_AD) were collected from a municipal wastewater treatment plant (WWTP), in which the TN concentration of effluent was less than 1.5 mg·L^-1, and their microbial community structure and function profiles were analyzed using 16S rRNA gene high-throughput sequencing. The microorganisms in WLK_AD had lower evenness compared with that in WLK_OD, which was attributed to environmental selection. Furthermore, PCoA revealed that different incoming wastewaters had an impact on microbial community structure. At the phylum level, Proteobacteria (70.11%) was enriched in WLK_AD. At the genus level, Thauera, Flavobacterium, Hydrogenophaga, and Zoogloea served as distinct-dominant denitrifying bacteria in WLK_AD; however, Trichococcus (3.50%) and Terrimonas (1.10%) were enriched in WLK_OD. Through the comparison between groups (P<0.05), the biomarkers detected in each WWTP were different. Furthermore, the results of the co-occurrence network showed that the bacteria from module I had a higher proportion in WLK_AD; the bacteria from module II had a higher proportion in WLK_OD, and they were common microorganisms in WWTPs, implying that wastewater environments drpve the differences in the microbial community structure. Among the types of environmental parameters, the removal efficiency of COD and TN had the greatest impact on the microbial community by the RDA. The removal efficiency of COD was positively correlated with the dominant bacteria from WLK_OD, such as Saccharibacteria, Thermomarinilinea, Terrimonas, and Comamonas; the removal efficiency of TN was positively correlated with the denitrifying bacteria from WLK_AD, such as Dokdonella, Thauera, Flavobacterium, and Zoogloea. WLK_AD was enriched with Novosphingobium, Dokdonella, Thauera, and Sphingomonas, which synergistically removed TN, leading to the TN of the effluent being less than 1.5 mg·L^-1. Moreover, based on the results of function prediction, WLK_AD had a higher proportion of genes that could code the denitrification enzymes.

Microbial Diversity and Community Composition of Duodenum Microbiota of High and Low Egg-Yielding Taihang Chickens Identified Using 16S rRNA Amplicon Sequencing

The duodenum is an important digestive organ for poultry and houses a variety of microbes that help chickens to enhance nutrient absorption and improve production. To evaluate the characteristic of gut microbiome, duodenum content samples from 42-week-old native Taihang chickens with high (H) and low (L) egg-yielding were collected for 16S rRNA amplicon sequencing analysis. Consequently, 1,361,341 sequences were clustered into 2055 OTUs, with percentages of affiliation of 96.50 and 57.30% at phylum and genus levels. Firmicutes, Proteobacteria, Cyanobacteria and Bacteroidetes were the dominant phylum, with a lower ratio of Firmicutes/Bacteroidetes in H group than in L group (p < 0.05). At genus level, overrepresentation of Bacteroides, Faecalibacterim, and Enterococcus and underrepresentation of Romboutsia were found in H group. No significant difference in overall diversity of microbiota was observed between two groups. LEFSe analysis revealed Enterococcus was significantly enriched in H group. Importantly, Enterococcus and Lactobacillus were negatively correlated. Functional prediction analysis showed the proportion of microbiota involved in the metabolism process was the highest and enriched in H group. Differences in microbiota composition between the two groups, which may be related to intestinal function difference, also provide promising biomarkers for improving laying hen production.

The Gut Microbiota Composition of Cnaphalocrocis medinalis and Their Predicted Contribution to Larval Nutrition

Intestinal bacterial flora plays an important role in the nutrition, physiology, and behavior of herbivorous insects. The composition of gut microbiota may also be affected by the food consumed. Cnaphalocrocis medinalis is an oligophagous pest, feeds on rice leaves almost exclusively and causes serious damage to rice in Asian countries. Using antibiotic treatment and metagenome sequencing, we investigated the influence of the food sources (rice and maize seedlings) on the structure and functions of intestinal bacteria of C. medinalis. Firstly, food utilization indices, relative growth rate (RGR), relative consumption rate (RCR), efficiency of conversion of ingested food (ECI), and efficiency of conversion of digested food (ECD), were all significantly adversely affected in the antibiotic treatment eliminating gut bacteria, showing that the microbiota loading in the gut were essential for the larva growth and development of C. medinalis. Further, metagenome sequencing revealed that different diets caused a variation in gut microbiota composition of C. medinalis, indicating that the gut microbiota were in part driven by the diet provided. However, the larvae of C. medinalis hosted a core microbial community in the gut, which was independent from the diets changing. The dominant bacteria in the two feeding groups were highly consistent in the gut of C. medinalis larvae, with the gut bacterial community dominated by Firmicutes at the phylum level, Enterococcus at the genus level, Enterococcus sp. FDAARGOS-375, E. casseliflavus, E. gallinarum, and E. sp. CR-Ec1 accounted for more than 96% of the gut microbiota. Functional prediction analysis demonstrated that gut bacteria encoded a series of metabolism-related enzymes involved in carbohydrate metabolism and amino acid synthesis. Carbohydrate metabolism was the most enriched function in both groups and was more abundant in rice feeding group than in maize feeding group. The core dominant Enterococcus species possessed complete pathways of 14 carbohydrates metabolism, 11 amino acids biosynthesis, and two vitamins synthesize, implied to contribute an essential role to the nutrition intake and development of C. medinalis. Finally, the study may provide an in-depth analysis of the symbiont-host co-adaptation and new insights into the management of C. medinalis.

[Structure and Functional Diversity of Bacterial Community in Rhizosphere Soil of Typical Vegetation in the Riparian Zone Along the Downstream of Songhua River]

The aim of this study was to provide a reference for the riparian zone with protection and ecological restoration by analyzing the differences in typical vegetation (Phragmites communis, Populus tomentosa, Salix sungkianica, and Carex schmidtii) rhizosphere bacterial communities and their functions and identifying the potential of different types of vegetation to restore the damaged riparian zone in Songhua River. The 16S rRNA of rhizosphere soil bacteria in the four typical vegetation types of the riparian zone along the downstream of the Songhua River was sequenced using the Illumina MiSeq PE300 high-throughput sequencing platform. The community diversity, functional differences, and influencing factors of rhizosphere soil bacteria for different vegetation types were analyzed. The results showed that the Ace index, Chao1 index, and Shannon index of soil bacterial diversity in P.communis were significantly higher than those of P.tomentosa (P<0.05), and there was no significant difference between the above two types of vegetation and S. sungkianica and C.schmidtii. There were significant differences between the soil bacterial community structure of P. tomentosa and that of the three other vegetation types (P<0.05). The soil bacterial community structures of S.sungkianica, C.schmidtii, and P.communis were similar. Bacteria in the rhizosphere soil of the four typical vegetation types could be divided into 38 phyla. Acidobacteria, Actinobacteria, Chloroflexi, Verrucomicrobia, and Proteobacteria were the dominant phyla (relative abundance>5%), and the Nitrospirae, Gemmatimonadetes, Bacteroidetes, Firmicutes, and Rokubacteria of bacteria had a relative abundance greater than 1%. The bacterial community in the rhizosphere soil of the four typical vegetation types had 6 primary metabolic pathways and 43 secondary metabolic pathways, including 14 types of main secondary metabolic pathways (relative abundance>1%). Diversity in rhizosphere soil bacterial communities of different vegetation types was significantly influenced by the C/N ratio, soil pH, and moisture content. Hence, the effects of different vegetation types in repairing the degraded riparian zone were different, and wetland vegetation (S.sungkianica and C.schmidtii) was conducive to the improvement in soil bacterial diversity and soil ecosystem functions.

[Soil bacterial community characteristics and ecological function prediction of alfalfa and crop rotation systems in the Loess Plateau, Northwest China]

In order to understand the effects of lucerne cropping rotation on the bacterial community of loess soil, a long-term field experiment was conducted in rain-fed agricultural area of Loess Plateau. The cropping systems included continuous lucerne (Medicago sativa, LC), lucerne removed and rotated with spring wheat (Triticum aestivum, L_FW), lucerne removed and rotated with corn (Zea mays, L_FC), lucerne removed and rotated with potato (Solanum tuberosum, LP), and lucerne removed and rotated with continuous millet (Panicum miliaceum, LM). Based on 16S rRNA high-throughput sequencing technology, we investigated soil bacterial community structure and diversity in different cropping systems, and predicted ecological function using PICRUSt method. The results showed that the dominant phyla of loess soil bacteria were Actinomycetes (20.3%-32.0%), Proteobacteria (19.2%-23.0%), Acidobacteria (12.4%-14.2%) and Chloroflexus (11.0%-12.7%). The dominant genus was Bacillus (1.9%) in lucerne-corn system and Pseudarthrobacter (2.5%) in other treatments. Rotation with annual crops decreased the relative abundance of Actinobacteria and increased that of Chloroflexi and Firmicutes. Redundancy analysis showed that the main soil factors driving soil bacterial community structure were nitrate, ammonium, and total nitrogen. PICRUSt function prediction results showed that metabolism (78.6%-79.1%) was the main function of soil bacterial communities in loess soil. Rotation with continued annual crops significantly decreased the abundance of soil bacterial carbohydrate metabolism functional genes, and significantly increased the abundance of functional genes for soil bacterial cofactors and vitamin metabolism, neurodegenerative diseases, and immune system. In conclusion, lucerne removed and rotated with continuous annual crops changed soil bacterial community structure and ecological functions. This study provided theoretical reference to explore succession characteristics of soil bacteria and to select succeeding crops for alfalfa in loess soil.

Storage Temperature Is More Effective Than Lactic Acid Bacteria Inoculations in Manipulating Fermentation and Bacterial Community Diversity, Co-Occurrence and Functionality of the Whole-Plant Corn Silage

The objective of this study was to investigate effects of different lactic acid bacteria (LAB) on the fermentation process of whole-plant corn silage stored at different temperatures based on bacterial community successions, interaction networks, and predicted functions. Before ensiling, whole-plant corn was inoculated with L. plantarum (LP) or L. buchneri (LB) and the silage bags were stored at 20 or 30°C, and sampled after 0.5, 1, 3, 7, 14, and 60 d of ensiling. The higher abundances of Leuconostoc, Pedicoccus and Weissella were observed in silage stored at 30°C after 12 h of ensiling, thereby rapidly decreased pH to about 4.5. According to meta-network analysis, the bacterial communities were more sensitive to storage temperature than LAB inoculants during whole-plant corn ensiling. Species of Lactobacillus and Weissella were sensitive to 30°C, while Leuconostoc species were sensitive to 20°C in whole-plant corn silage. The storage temperature of 30°C decreased bacterial diversity and network complexity of whole-plant corn silage compared with 20°C. Additionally, LP inoculation changed the bacterial community successions during the early and middle ensiling periods, while LB inoculation affected bacterial community successions in the later stage of ensiling. The metabolic pathways of bacterial community were totally different in LB-inoculated silage from that in control and LP-inoculated silage. As the bacterial compositions became simple along with the ensiling process, the functional structure of bacterial community became simplified as well. In general, the storage temperature had a greater impact on the fermentation characteristics, bacterial community and predicted function of whole-plant corn silage compared with LAB inoculations.

IMPORTANCE Increased understanding of effects of regulation measures on whole-plant corn silage is important from bacterial community succession, interaction network and predicted functions. According to alpha diversity and meta co-occurrence network, the bacterial communities were more sensitive to storage temperature than LAB inoculants during whole-plant corn ensiling. The storage temperature of 30°C decreased bacterial diversity and network complexity of whole-plant corn silage compared with 20°C. In addition, 30°C promoted the initiation of LP and LB inoculants, and 20°C was conducive to the long-term growth of LP and LB inoculants. According to the changes of bacterial community and predicated functions, it was further confirmed that the effect of LB inoculation was more obvious on whole-plant corn silage.

[Characteristics of Bacterial Community Structure in Wuliangsu Lake During an Irrigation Interval in Hetao Plain]

In order to study the bacterial community composition and corresponding function in Wuliangsu Lake at the end of the Hetao Plain during the irrigation gap period, lake samples were collected in September 2020, and the pH, TN, TP, DIP, DTP, NH₄⁺-N, Chla, EC, SAL, and other indicators were analyzed. The 16S rRNA high-throughput sequencing method was used to explore the attached bacteria and bacterioplankton in 15 samples of the surface water in Wuliangsu Lake. The experimental results showed that:① the alpha diversity Chao and Shannon indices of attached bacteria were greater than that of bacterioplankton, but the median of Shannoneven index was the same. ② In each sampling point, the bacterioplankton of Proteobacteria and Actinobacteria in the top five dominant bacteria phyla were higher than that of attached bacteria, and the abundance of attached bacteria and bacterioplankton of Bacteroidota were staggered. On the contrary, the contents of attached bacteria of Verrucomicrobiota and Cyanobacteria were all higher than that of bacterioplankton. ③ Redundant analysis showed that pH had the most significant effect on dominant attached bacteria, and the effect of conductivity and salinity in dominant bacterioplankton was the most significant. ④ PICRUSt2 function prediction analysis showed that attached bacteria and planktonic bacteria had the strongest metabolic functions, showing abundant metabolic functions. There were 29 nitrogen-related effective KOs and 88 phosphorus-related effective KOs, with the greatest nitrogen-fixing function and strong inorganic phosphorus-dissolving function, and bacterioplankton played a greater role in the two functions.

Alterations of the Gut Microbiota in Response to Total Sleep Deprivation and Recovery Sleep in Rats

INTRODUCTION

Accumulating evidence suggests that both sleep loss and gut dysbiosis can lead to metabolic disorders. However, less is known about the impact of total sleep deprivation (SD) and sleep recovery on the composition, function, and metabolic dynamics of the gut microbiota.

METHODS

Specific-pathogen free Sprague-Dawley rats were subjected to 48 h of SD with gentle handling and then allowed to recover for 1 week. Taxonomic profiles of fecal microbiota were obtained at baseline, 24 h of SD, 48 h of SD, and 1 week of recovery. We used 16S rRNA gene sequencing to analyze the gut microbial composition and function and further characterize microbiota-derived metabolites in rats.

RESULTS

The microbiota composition analysis revealed that gut microbial composition and metabolites did not change in the rats after 24 h of SD but were significantly altered after 48 h of SD. These changes were reversible after 1 week of sleep recovery. A functional analysis was performed based on Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations, indicating that 19 KEGG pathways were significantly altered in the gut microbiota in SD rats. These functional changes occurred within 24 h of SD, were more apparent after 48 h of SD, and did not fully recover after 1 week of sleep recovery.

CONCLUSION

These results indicate that acute total SD leads to significant compositional and functional changes in the gut microbiota, and these changes are reversible.

Evaluation of model refinement in CASP14

We report here an assessment of the model refinement category of the 14th round of Critical Assessment of Structure Prediction (CASP14). As before, predictors submitted up to five ranked refinements, along with associated residue-level error estimates, for targets that had a wide range of starting quality. The ability of groups to accurately rank their submissions and to predict coordinate error varied widely. Overall, only four groups out-performed a "naïve predictor" corresponding to the resubmission of the starting model. Among the top groups, there are interesting differences of approach and in the spread of improvements seen: some methods are more conservative, others more adventurous. Some targets were "double-barreled" for which predictors were offered a high-quality AlphaFold 2 (AF2)-derived prediction alongside another of lower quality. The AF2-derived models were largely unimprovable, many of their apparent errors being found to reside at domain and, especially, crystal lattice contacts. Refinement is shown to have a mixed impact overall on structure-based function annotation methods to predict nucleic acid binding, spot catalytic sites, and dock protein structures.

Endophytic Bacterial Communities of Ginkgo biloba Leaves During Leaf Developmental Period

Plant-specialized secondary metabolites have ecological functions in mediating interactions between plants and their entophytes. In this study, high-throughput gene sequencing was used to analyze the composition and abundance of bacteria from Ginkgo leaves at five different sampling times. The results indicated that the bacterial community structure varied during leaf developmental stage. Bacterial diversity was observed to be the highest at T2 stage and the lowest at T1 stage. Proteobacteria, Firmicutes, Actinobacteria, Chloroflexi, Cyanobacteria, and Bacteroidetes were found as the dominant phyla. The major genera also showed consistency across sampling times, but there was a significant variation in their abundance, such as Bacillus, Lysinibacillus, and Staphylococcus. Significant correlations were observed between endophytic bacteria and flavonoids. Especially, Staphylococcus showed a significant positive correlation with quercetin, and changes in the abundance of Staphylococcus also showed a strong correlation with flavonoid content. In order to determine the effect of flavonoids on endophytic bacteria of Ginkgo leaves, an extracorporeal culture of related strains (a strain of Staphylococcus and a strain of Deinococcus) was performed, and it was found that the effect of flavonoids on them remained consistent. The predicted result of Tax4Fun2 revealed that flavonoids might lead to a lower abundance of endophytic microorganisms, which further proved the correlation between bacterial communities and flavonoids. This study provided the first insight into the bacterial community composition during the development of Ginkgo leaves and the correlation between the endophytic bacteria and flavonoids.

Alterations of oral microbiota in patients with panic disorder

The main characteristics of panic disorder (PD) include recurrent panic attacks and persistent worry, accompanied by other physical and cognitive symptoms. While recent studies have revealed that gut bacteria play an important role in anxiety and depression, little is known about the relationship between oral microbiota and PD. Therefore, the objective of this study was to explore a possible correlation between oral microbiota and PD. We conducted 16S rRNA sequencing to compare differences in the oral microbiota of patients with PD (n = 26) and healthy controls (n = 40). Patients with PD exhibited higher alpha diversity (abundance and evenness) in their oral microbiota than healthy controls, while analysis of beta diversity revealed that the two groups differed in microbial community composition. Moreover, the relative abundance of 61 genera differed between them. Overall, PD resulted in distinct oral microbial profiles that could be potential diagnostic markers and therapeutic targets.

D-SCRIPT translates genome to phenome with sequence-based, structure-aware, genome-scale predictions of protein-protein interactions

We combine advances in neural language modeling and structurally motivated design to develop D-SCRIPT, an interpretable and generalizable deep-learning model, which predicts interaction between two proteins using only their sequence and maintains high accuracy with limited training data and across species. We show that a D-SCRIPT model trained on 38,345 human PPIs enables significantly improved functional characterization of fly proteins compared with the state-of-the-art approach. Evaluating the same D-SCRIPT model on protein complexes with known 3D structure, we find that the inter-protein contact map output by D-SCRIPT has significant overlap with the ground truth. We apply D-SCRIPT to screen for PPIs in cow (Bos taurus) at a genome-wide scale and focusing on rumen physiology, identify functional gene modules related to metabolism and immune response. The predicted interactions can then be leveraged for function prediction at scale, addressing the genome-to-phenome challenge, especially in species where little data are available.

Response of soil bacterial community structure and function under two salt-tolerant plants in a coastal saline soil area of eastern Hebei province of China

The plants Feicai (Sedum aizoon L.) and dandelion(Taraxacum mongolicum Hand.-Mazz.) have good salt tolerance, and can improve soil quality and the micro-ecological environment. Coastal saline-soil plots planted with S. aizoon and T. mongolicum and bare plots were used to explore their effects on the microbial community structure of coastal saline soil. The diversity and function of soil bacterial communities were analyzed using Illumina MiSeq high-throughput sequencing technology. The results showed that the α-diversity of soil bacterial communities were higher in planted than in bare plots, in the following order: T. mongolicum plot > S. aizoon plot > bare plot. The soil bacterial communities also changed after planting S. aizoon and T. mongolicum. The LDA effect size analysis showed that there were 37 indicator species among the three plot types. Correlation analysis of environmental factors showed that EC, AP, and OM were the main factors influencing bacterial community composition in this coastal saline soil. The PICRUSt functional prediction showed that the numbers of metabolic functions of bacterial communities were in the following order: T. mongolicum plot > S. aizoon plot > bare plot. The results provide a theoretical basis and plant species for developing salt-tolerant bacterial resources and phytoremediation of coastal saline soil.

[Characteristics of Bacterial Community Structure in Fluvo-aquic Soil Under Different Rotation Fallow]

The aim of this study was to provide a reference for promoting ecological restoration of farmland and the green development of agriculture in the alluvial plain of the lower Yellow River by determining the effects of different rotation fallow patterns on the bacterial community of the fluvo-aquic soil. Farmland soil subject to a long-term rotation fallow experiment since 2018 was studied using Illumina MiSeq high-throughput sequencing technology, and the 'Tax4Fun' bacterial function prediction tool was used to analyze differences in soil bacterial community structure and function under the following four rotation fallow regimes:long fallow(LF), winter wheat and summer fallow(WF), winter fallow and summer maize(FM), and annual rotation of winter wheat and summer maize(WM). The environmental factors affecting changes in the soil bacterial community structure and function were also analyzed. In total, 44 phyla, 146 classes, 338 orders, 530 families, 965 genera, and 2073 species of bacteria were detected in the soil samples from the different rotation fallow regimes, and the dominant bacterial groups were Actinobacteria, Proteobacteria, Acidobacteria, and Chloroflexi in 0-20 cm and 20-40 cm soil layers. However, the relative abundances of the dominant bacteria groups were varied between the rotation fallow regimes. In the 0-20 cm layer of the seasonal fallow soils(WF and FM), bacteria were more abundant and community diversity was higher than that of the WM and LF soils. In 20-40 cm soil layer, the WF soil was more abundant in bacterial and the community was more diverse. Based on the prediction function of the 'Tax4Fun' tool, six primary metabolic pathways, 40 secondary metabolic pathways(18 types with relative abundance greater than 1%), and 264 tertiary metabolic pathways were identified in the soil bacteria of the different rotation fallow regimes. Seasonal fallow(WF and FM) was found to increase the relative abundance of beneficial bacterial metabolic pathways involved in metabolism, environmental information processing, and genetic information processing. According to RDA analysis, the soil bacterial community in the 0-20 cm soil layer was significantly affected by soil moisture, total phosphorus, available phosphorus, available potassium, pH, and C/N ratio(P<0.05), and the soil bacterial community in 20-40 cm soil layer was significantly affected by soil total phosphorus and available phosphorus(P<0.05). Therefore, different fallow patterns were linked to variation in the structure, diversity, and metabolic functions of soil bacterial communities. Based on these results, seasonal fallow practices could promote the health and stability of farmland soil ecosystems.

Multivariate Analysis in Microbiome Description: Correlation of Human Gut Protein Degraders, Metabolites, and Predicted Metabolic Functions

Protein catabolism by intestinal bacteria is infamous for releasing many harmful compounds, negatively affecting the health status, both locally and systemically. In a previous study, we enriched in protein degraders the fecal microbiota of five subjects, utilizing a medium containing protein and peptides as sole fermentable substrates and we monitored their evolution by 16S rRNA gene profiling. In the present study, we fused the microbiome data and the data obtained by the analysis of the volatile organic compounds (VOCs) in the headspace of the cultures. Then, we utilized ANOVA simultaneous component analysis (ASCA) to establish a relationship between metabolites and bacteria. In particular, ASCA allowed to separately assess the effect of subject, time, inoculum concentration, and their binary interactions on both microbiome and volatilome data. All the ASCA submodels pointed out a consistent association between indole and Escherichia–Shigella, and the relationship of butyric, 3-methyl butanoic, and benzenepropanoic acids with some bacterial taxa that were major determinants of cultures at 6 h, such as Lachnoclostridiaceae (Lachnoclostridium), Clostridiaceae (Clostridium sensu stricto), and Sutterellaceae (Sutterella and Parasutterella). The metagenome reconstruction with PICRUSt2 and its functional annotation indicated that enrichment in a protein-based medium affected the richness and diversity of functional profiles, in the face of a decrease of richness and evenness of the microbial community. Linear discriminant analysis (LDA) effect size indicated a positive differential abundance (p < 0.05) for the modules of amino acid catabolism that may be at the basis of the changes of VOC profile. In particular, predicted genes encoding functions belonging to the superpathways of ornithine, arginine, and putrescine transformation to GABA and eventually to succinyl-CoA, of methionine degradation, and various routes of breakdown of aromatic compounds yielding succinyl-CoA or acetyl-CoA became significantly more abundant in the metagenome of the bacterial community.

[Effect of Chelated Iron on Nitrogen Removal Efficiency and Microbial Community Structure in the Anaerobic Ferric Ammonium Oxidation]

In order to understand the characteristics and interactions of the microbial community during the anaerobic ferric ammonium oxidation (FEAMMOX) process, this study investigated the effects of various forms of chelated iron on nitrogen removal efficiency and microbial community structure. After 77 days of reactor operation, the removal efficiency of total nitrogen was 83.32% for the ferric humate group, 43.67% for the ferric citrate group, 55.07% for the ferric sodium ethylene diamine tetraacetate group, and 12.65% for the ferric ammonium triacetate group. After the experiment, the abundance of denitrifying bacteria Comamonadaceae in ferric humate group was 17.57%, the abundance of Clostridium in ferric citrate group was 47.70%; and the abundance of denitrifying bacteria Thermomonas in the ferric sodium ethylene diamine tetraacetate group was 20.11%. This indicates that ferric humate is a more effective electron acceptor for the FEAMMOX process. The result of function prediction shows that the iron, sulfur, and nitrogen cycles are all closely related, with iron and sulfur metabolism playing an important role in nitrogen removal. In the humate group, iron respiration and the nitrogen cycle are more strongly correlated than other groups. Co-occurrence network analysis showed that the keystone species in the FEAMMOX process is Tessaracoccus.

Comparative Genomic Analysis of the DUF34 Protein Family Suggests Role as a Metal Ion Chaperone or Insertase

Members of the DUF34 (domain of unknown function 34) family, also known as the NIF3 protein superfamily, are ubiquitous across superkingdoms. Proteins of this family have been widely annotated as "GTP cyclohydrolase I type 2" through electronic propagation based on one study. Here, the annotation status of this protein family was examined through a comprehensive literature review and integrative bioinformatic analyses that revealed varied pleiotropic associations and phenotypes. This analysis combined with functional complementation studies strongly challenges the current annotation and suggests that DUF34 family members may serve as metal ion insertases, chaperones, or metallocofactor maturases. This general molecular function could explain how DUF34 subgroups participate in highly diversified pathways such as cell differentiation, metal ion homeostasis, pathogen virulence, redox, and universal stress responses.

iAMP-CA2L: a new CNN-BiLSTM-SVM classifier based on cellular automata image for identifying antimicrobial peptides and their functional types

Predicting antimicrobial peptides (AMPs') function is an important and difficult problem, particularly when AMPs have many multiplex functions, i.e. some AMPs simultaneously have two or three functional classes. By introducing the 'CNN-BiLSTM-SVM classifier' and 'cellular automata image', a new predictor, called iAMP-CA2L, has been developed that can be used to deal with the systems containing both monofunctional and multifunctional AMPs. iAMP-CA2L is a 2-level predictor. The 1st level is to identify whether a given query peptide is an AMP or a non-AMP, while the 2nd level is to predict if it belongs to one or more functional types. As demonstration, the jackknife cross-validation was performed with iAMP-CA2L on a benchmark dataset of AMPs classified into the following 10 functional classes: (1) antibacterial peptides, (2) antiviral peptides, (3) antifungal peptides, (4) antibiofilm peptides, (5) antiparasital peptides, (6) anti-HIV peptides, (7) anticancer (antitumor) peptides, (8) chemotactic peptides, (9) anti-MRSA peptides and (10) antiendotoxin peptides, where none of AMPs included has ≥90% pairwise sequence identity to any other in the same subset. Experiments show that iAMP-CA2L has greatly improved the prediction performance compared with the existing predictors. iAMP-CA2L is freely accessible to the public at the web site http://www.jci-bioinfo.cn/ iAMP-CA2L, and the predictor program has been uploaded to https://github.com/liujin66/iAMP-CA2L.

Seasonal Variation in Gut Microbiota Related to Diet in Fejervarya limnocharis

Organisms adapt to environmental fluctuations by varying their morphology and structural, physiological, and biochemical characteristics. Gut microbiome, varying rapidly in response to environmental shifts, has been proposed as a strategy for adapting to the fluctuating environment (e.g., new dietary niches). Here, we explored the adaptive mechanism of frog intestinal microbes in response to environmental changes. We collected 170 Fejervarya limnocharis during different seasons (spring, summer, autumn, and pre-hibernation) to study the compositional and functional divergence of gut microbiota and analysed the effects of seasonal feeding habits and body condition on intestinal microorganisms using 16S rRNA high-throughput sequencing, Tax4Fun function prediction analysis, and bioinformatics analysis. The results showed no significant dietary difference in various seasons and between males and females. However, a significantly positive correlation was detected between dietary diversity and food niche width. Host condition (body size, body mass, and body condition) also revealed seasonal changes. The frogs were colonised by 71 bacterial phyla and dominated by Proteobacteria, Firmicutes, and Bacteroidetes. Stenotrophomonas was the most abundant genus in the Proteobacteria. The composition, diversity, and function of intestinal microorganisms in different seasons were significantly different. Significant differences were observed in composition and function but not in the microbial diversity between sexes. Furthermore, seasonal foods and body mass were significantly correlated with gut microbial composition. Our results suggest that gut microbiomes of F. limnocharis vary seasonally in response to diet under fluctuating environments.

The role of the vaginal microbiome in distinguishing female chronic pelvic pain caused by endometriosis/adenomyosis

Background

This study aimed to investigate the specific vaginal microbiome in the differential diagnosis of endometriosis/adenomyosis (EM/AM)-associated chronic pelvic pain (CPP) from other types of CPP, and to explore the role of the vaginal microbiome in the mechanism of EM/AM-associated CPP.

Methods

We recruited 37 women with EM/AM-associated CPP, 25 women with chronic pelvic pain syndrome (CPPS) without EM/AM, and 66 women without CPPS into our study. All of the participants were free from human papillomavirus (HPV) infection. Sequencing of barcoded 16S rRNA gene fragments (V4) was used to determine the vaginal microbiome composition on the Illumina HiSeq2500 System. Taxonomic and functional bioinformatics analyses were performed using t-test, linear discriminant analysis effect size (LEfSe), MetaStat, and PICRUSt algorithms.

Results

At the species level, EM/AM-associated CPP was found to be associated with a predominance of Clostridium butyricum, Clostridium disporicum, Alloscardovia omnicolens, and Veillonella montpellierensis, and a concomitant paucity of Lactobacillus jensenii, Lactobacillus reuteri, and Lactobacillus iners. When the relative abundance of Clostridium disporicum was over 0.001105% and that of Lactobacillus reuteri was under 0.1911349%, the differential diagnostic sensitivity and specificity were 81.08% and 52.0%, respectively. When serum CA125 was combined, the sensitivity increased to 89.19%, but the specificity remained at 52.0%. The PICRUSt results identified 7 differentially regulated pathways within the 3 groups that may be of relevance.

Conclusions

Compared to that of CPPS patients without EM/AM and women without CPPS, the vaginal microbiome of patients with EM/AM-associated CPP shows significantly higher alpha (phylogenetic) diversity, as well as higher counts of Clostridium butyricum, Clostridium disporicum, Alloscardovia omnicolens, and Veillonella montpellierensis. These differences in the vaginal microbiome may interfere with local functional pathways, which could provide a direction for innovative metabolite-specific targeted treatment. The combination of vaginal biomarkers and serum CA125 may provide an original method to differentiate EM/AM-associated CPP.

[Effects of Land Use Changes on Soil Fungal Community Structure and Function in the Riparian Wetland Along the Downstream of the Songhua River]

The aim of this study was to provide a reference for wetland resource management and ecological restoration by analyzing the influence of land use changes on the soil fungal community and its function and to identify the potential natural restoration ability of degraded riverside wetlands in the Songhua River. In July 2018, soil fungi in a natural wetland, paddy field, sand mining slash, and restoration wetland along the downstream of the Songhua River were amplified by PCR. PCR products were sequenced using the Illumina MiSeq PE300 high-throughput sequencing platform. The differences in the soil fungal community composition and function and its influencing factors were analyzed. The results showed that the α-diversity indexes of soil fungi were significantly reduced by sand mining or cultivation in the natural wetland (P<0.05). The ACE index and Chao1 index of soil fungi in the sand mining slash were significantly improved after the sand mining area was restored to a constructed wetland (P<0.05). There were significant differences in the soil fungal community structure between the paddy field and other land use types (P<0.05). The soil fungi in the riparian wetland could be divided into 16 phyla. Ascomycota, Basidiomycota, Mortierellomycota, and Rozellomycota were the dominant phyla (relative abundance>1%). Ectomycorrhizal was the main functional fungus in the natural wetland and restoration wetland with the supplementation of bryophyte parasites and lichen parasites. Litter saprotrophs and soil saprotrophs were the main functional groups of fungi in the paddy field and sand mining slash, and the relative abundances of animal pathogens and plant pathogens increased significantly in the paddy field. The diversity of the soil fungal community was significantly influenced by the soil pH, organic carbon, total nitrogen, and total phosphorus contents. Thus, resource development in the natural riparian wetlands reduced the ecosystem stability and increased the potential ecological risks.

Beneficial Effect of Alkaloids From Sophora alopecuroides L. on CUMS-Induced Depression Model Mice via Modulating Gut Microbiota

It was recently shown that the gut microbiota of both depression patients and depression model animals is significantly altered, suggesting that gut microbes are closely related to depression. Here, we investigated the effects of Sophora alopecuroides L.-derived alkaloids on the gut microbiota of mice with depression-like behaviors. We first established a mouse model of depression via chronic unpredictable mild stress (CUMS) and detected changes in depression-like behaviors and depression-related indicators. Simultaneously, 16S rRNA sequencing was performed to investigate gut microbiota changes. Sophora alopecuroides L.-derived alkaloids improved depression-like behaviors and depression-related indicators in mice. The alkaloids decreased the gut microbiota diversity of CUMS mice and depleted intestinal differentially abundant "harmful" microbiota genera. Spearman analysis showed that there is a certain correlation between the differential microbiota (Lactobacillus, Helicobacter, Oscillospira, Odoribacter, Mucispirillum, Ruminococcus), depression-like behaviors, and depression-related indicators. Combined with the predictive analysis of gut microbiota function, these results indicate that alkaloids improve depression in mice through modulating gut microbiota.

In Silico Analysis of Huntingtin Homologs in Lower Eukaryotes

Huntington’s disease is a rare neurodegenerative and autosomal dominant disorder. HD is caused by a mutation in the gene coding for huntingtin (Htt). The result is the production of a mutant Htt with an abnormally long polyglutamine repeat that leads to pathological Htt aggregates. Although the structure of human Htt has been determined, albeit at low resolution, its functions and how they are performed are largely unknown. Moreover, there is little information on the structure and function of Htt in other organisms. The comparison of Htt homologs can help to understand if there is a functional conservation of domains in the evolution of Htt in eukaryotes. In this work, through a computational approach, Htt homologs from lower eukaryotes have been analysed, identifying ordered domains and modelling their structure. Based on the structural models, a putative function for most of the domains has been predicted. A putative C. elegans Htt-like protein has also been analysed following the same approach. The results obtained support the notion that this protein is a orthologue of human Htt.

Network-based methods for gene function prediction

The rapid development of high-throughput technology has generated a large number of biological networks. Network-based methods are able to provide rich information for inferring gene function. This is composed of analyzing the topological characteristics of genes in related networks, integrating biological information, and considering data from different data sources. To promote network biology and related biotechnology research, this article provides a survey for the state of the art of advanced methods of network-based gene function prediction and discusses the potential challenges.

Microbial community and metabolic function analysis of cigar tobacco leaves during fermentation

Cigar tobacco leaves (CTLs) contain abundant bacteria and fungi that are vital to leaf quality during fermentation. In this study, artificial fermentation was used for the fermentation of CTLs since it was more controllable and efficient than natural aging. The bacterial and fungal community structure and composition in unfermented and fermented CTLs were determined to understand the effects of microbes on the characteristics of CTLs during artificial fermentation. The relationship between the chemical contents and alterations in the microbial composition was evaluated, and the functions of bacteria and fungi in fermented CTLs were predicted to determine the possible metabolic pathways. After artificial fermentation, the bacterial and fungal community structure significantly changed in CTLs. The total nitrate and nicotine contents were most readily affected by the bacterial and fungal communities, respectively. FAPROTAX software predictions of the bacterial community revealed increases in functions related to compound transformation after fermentation. FUNGuild predictions of the fungal community revealed an increase in the content of saprotrophic fungi after fermentation. These data provide information regarding the artificial fermentation mechanism of CTLs and will inform safety and quality improvements.

Identification, biogenesis and function prediction of novel circRNA during the chicken ALV-J infection

Circular RNA (circRNA) is a new non-coding RNA with a highly conserved and stable covalently closed loop structure, and it plays an important role in a variety of biological processes and the occurrence of diseases. Based on the sequencing results, circRNA_3079 had the most significant difference between the infected group and normal group, up to about 8 times. It has attracted our attention and was selected for further verification and analysis. Though the characteristics analysis of circRNA_3079 in chicken, we found circRNA_3079 is a stable, circular transcript, which mainly exists in the cytoplasm. And it is widely expressed in various tissues of chickens, and highly expressed in lung, spleen, lymph and bursa of fabricius. Bioinformatics analysis results showed that circRNA_3079 and the predicted target genes are enriched in many pathways related to immunity or tumors, such as p53 signaling pathway, Jak-STAT signaling pathway and NOD-like receptor signaling pathway, which revealed that circRNA_3079 may indirectly regulate the ALV-J infection process through the regulation of target genes.HIGHLIGHTSCircRNA_3079 is an abundant and stable circular RNA expressed in different tissues and cells in chicken.The circularization of circRNA_3079 does not depend on the reverse complementary repetitive sequence of the flanking sequence.CircRNA_3079 may indirectly regulate the ALV-J infection process.

[Effects of Land Use Changes on Soil Bacterial Community Diversity in the Riparian Wetland Along the Downstream of Songhua River]

The aim of this study was to provide a theoretical basis for the restoration of degraded wetlands in the Songhua River by determining the effect of habitat quality changes on the soil bacterial community. The 16S rDNA of soil bacteria in five land use types (natural wetland, paddy field, corn field, sand mining slash, restoration wetland) of the riparian wetland along the downstream of the Songhua River was sequenced using the Illumina MiSeq PE300 high-throughput sequencing platform. The differences in the community diversity and functions of soil bacteria for different land use types were analyzed. ACE, Chao1, and Shannon indices of soil bacterial diversity were significantly reduced by reclaiming the wetland into the corn field (P<0.05), and they were significantly improved by wetland restoration in the sand mining slash (P<0.05). The differences in the soil bacterial community structure were significant among natural wetlands, paddy fields, corn fields, and sand mines (P<0.05). Similar bacterial community structures were found in sand mining slash and restoration wetlands. Soil bacteria in the riparian wetland can be divided into 40 phyla, 105 classes, 258 orders, 421 families, 802 genera, and 1673 species. Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Bacteroidetes, Verrucomicrobia, Firmicutes, and Gemmatimonadetes were the dominant phyla (relative abundance>1%). In contrast, Bacteroidetes preferred the soil under the paddy environment, Proteobacteria and Gemmatimonadales preferred the soil environment of corn, and Actinobacteria preferred the soil environment of sand mining slash. Wetland soil bacteria have six primary metabolic pathways (metabolism, environmental information processing, genetic information processing, cellular processes, human disease, and organismal systems) and 46 secondary metabolic pathways including 19 types of main secondary metabolic pathways (relative abundance>1%). Diversity of the soil fungal community was significantly influenced by soil pH, moisture content, available nitrogen, and the C/N ratio. Hence, potential ecological risks increased and ecosystem stability decreased because of the resource development activities in natural wetlands. Diversity of the soil fungal community plays a critical role in protecting the ecological security and supplying considerable amounts of undeveloped resources.

Aerobic Denitrification Microbial Community and Function in Zero-Discharge Recirculating Aquaculture System Using a Single Biofloc-Based Suspended Growth Reactor: Influence of the Carbon-to-Nitrogen Ratio

In this study, the effect of aerobic denitrification on nitrogen removal was investigated using two zero-discharge biofloc-based recirculating aquaculture systems with representative carbon-to-nitrogen (C/N) ratios of 15 (CN15) and 20 (CN20). Aquaculture wastewater, residual feed, and fish feces were treated in an aerated suspended growth reactor (SGR, dissolved oxygen > 5.0 mg L^–1). Low toxic NH₃ (<0.1 mg L^–1) and NO₂^–-N (<0.5 mg L^–1) concentrations and high NO₃^–-N (83.3%) and NO₂^–-N (100%) removal efficiencies were achieved in the fish tank and SGR of CN20, respectively. The nitrogen mass balances indicated that the gaseous nitrogen loss accounted for 72–75% of the nitrogen input. Illumina sequencing and quantitative polymerase chain reaction revealed that increasing the C/N ratio significantly increased the amount of aerobic denitrifying bacteria (Dechloromonas, Rhodobacter, Flavobacterium, and Zoogloea) and aerobic denitrifying functional genes (napA, nirK, and nosZ). Autotrophic Nitrosomonas was the dominant nitrifying bacteria in the CN15 system, and autotrophic (Nitrosomonas) and heterotrophic nitrifiers coexisted in the CN20 system. Moreover, the functional prediction analysis showed that the carbohydrate, energy, and amino acid metabolisms in the SGR of the latter increased. In conclusion, aerobic denitrification should widely exist in biofloc systems.

Pseudo2GO: A Graph-Based Deep Learning Method for Pseudogene Function Prediction by Borrowing Information From Coding Genes

Pseudogenes are indicating more and more functional potentials recently, though historically were regarded as relics of evolution. Computational methods for predicting pseudogene functions on Gene Ontology is important for directing experimental discovery. However, no pseudogene-specific computational methods have been proposed to directly predict their Gene Ontology (GO) terms. The biggest challenge for pseudogene function prediction is the lack of enough features and functional annotations, making training a predictive model difficult. Considering the close functional similarity between pseudogenes and their parent coding genes that share great amount of DNA sequence, as well as that coding genes have rich annotations, we aim to predict pseudogene functions by borrowing information from coding genes in a graph-based way. Here we propose Pseudo2GO, a graph-based deep learning semi-supervised model for pseudogene function prediction. A sequence similarity graph is first constructed to connect pseudogenes and coding genes. Multiple features are incorporated into the model as the node attributes to enable the graph an attributed graph, including expression profiles, interactions with microRNAs, protein-protein interactions (PPIs), and genetic interactions. Graph convolutional networks are used to propagate node attributes across the graph to make classifications on pseudogenes. Comparing Pseudo2GO with other frameworks adapted from popular protein function prediction methods, we demonstrated that our method has achieved state-of-the-art performance, significantly outperforming other methods in terms of the M-AUPR metric.