A potential network structure of symbiotic bacteria involved in carbon and nitrogen metabolism of wood-utilizing insect larvae

Feed Components and Timing to Improve the Feed Conversion Ratio for Sustainable Aquaculture Using Starch

Aquaculture contributes to the sustainable development of food security, marine resource conservation, and economy. Shifting aquaculture feed from fish meal and oil to terrestrial plant derivatives may result in cost savings. However, many carnivorous fish cannot be sustained on plant-derived materials, necessitating the need for the identification of important factors for farmed fish growth and the identification of whether components derived from terrestrial plants can be used in feed. Herein, we focused on the carnivorous fish leopard coral grouper (P. leopardus) to identify the essential growth factors and clarify their intake timing from feeds. Furthermore, we evaluated the functionality of starch, which are easily produced by terrestrial plants. Results reveal that carbohydrates, which are not considered essential for carnivorous fish, can be introduced as a major part of an artificial diet. The development of artificial feed using starch offers the possibility of increasing the growth of carnivorous fish in aquaculture.

Developing a microbial community structure index (MCSI) as an approach to evaluate and optimize bioremediation performance

Much attention is placed on organohalide-respiring bacteria (OHRB), such as Dehalococcoides, during the design and performance monitoring of chlorinated solvent bioremediation systems. However, many OHRB cannot function effectively without the support of a diverse group of other microbial community members (MCMs), who play key roles fermenting organic matter into more readily useable electron donors, producing corrinoids such as vitamin B12, or facilitating other important metabolic processes or biochemical reactions. While it is known that certain MCMs support dechlorination, a metric considering their contribution to bioremediation performance has yet to be proposed. Advances in molecular biology tools offer an opportunity to better understand the presence and activity of specific microbes, and their relation to bioremediation performance. In this paper, we test the hypothesis that a specific microbial consortium identified within 16S ribosomal ribonucleic acid (rRNA) gene next generation sequencing (NGS) data can be predictive of contaminant degradation rates. Field-based data from multiple contaminated sites indicate that increasing relative abundance of specific MCMs correlates with increasing first-order degradation rates. Based on these results, we present a framework for computing a simplified metric using NGS data, the Microbial Community Structure Index, to evaluate the adequacy of the microbial ecosystem during assessment of bioremediation performance.

Alteration of shoaling behavior and dysbiosis in the gut of medaka (Oryzias latipes) exposed to 2-μm polystyrene microplastics

There is global concern that microplastics may harm aquatic life. Here, we examined the effects of fine polystyrene microplastics (PS-MPs, 2-μm diameter, 0.1 mg/L, 2.5 × 107 particles/L) on the behavior and the microbiome (linked to brain-gut interaction) of a fish model using medaka, Oryzias latipes. We found that shoaling behavior was reduced in PS-MP-exposed medaka compared with control fish during the exposure period, but it recovered during a depuration period. There was no difference in swimming speed between the PS-MP-exposed and control groups during the exposure period. Analysis of the dominant bacterial population (those comprising ≥1% of the total bacterial population) in the gut of fish showed that exposure to PS-MPs tended to increase the relative abundance of the phylum Fusobacteria and the genus Vibrio. Furthermore, structural-equation modeling of gut bacteria on the basis of machine-learning data estimated strong relationship involved in the reduction of the functional bacterial species of minority (<1% of the total bacterial population) such as the genera Muribaculum (an undefined role), Aquaspirillum (a candidate for nitrate metabolism and magnetotactics), and Clostridium and Phascolarctobacterium (potential producers of short-chain fatty acids, influencing behavior by affecting levels of neurotransmitters) as a group of gut bacteria in association with PS-MP exposure. Our results suggest that fish exposure to fine microplastics may cause dysbiosis and ultimately cause social behavior disorders linked to brain-gut interactions. This effect could be connected to reduction of fish fitness in the ecosystem and reduced fish survival.

Deciphering Microbial Community and Nitrogen Fixation in the Legume Rhizosphere

Nitrogen is the most limiting factor in crop production. Legumes establish a symbiotic relationship with rhizobia and enhance nitrogen fixation. We analyzed 1,624 rhizosphere 16S rRNA gene samples and 113 rhizosphere metagenomic samples from three typical legumes and three non-legumes. The rhizosphere microbial community of the legumes had low diversity and was enriched with nitrogen-cycling bacteria (Sphingomonadaceae, Xanthobacteraceae, Rhizobiaceae, and Bacillaceae). Furthermore, the rhizosphere microbiota of legumes exhibited a high abundance of nitrogen-fixing genes, reflecting a stronger nitrogen-fixing potential, and Streptomycetaceae and Nocardioidaceae were the predominant nitrogen-fixing bacteria. We also identified helper bacteria and confirmed through metadata analysis and a pot experiment that the synthesis of riboflavin by helper bacteria is the key factor in promoting nitrogen fixation. Our study emphasizes that the construction of synthetic communities of nitrogen-fixing bacteria and helper bacteria is crucial for the development of efficient nitrogen-fixing microbial fertilizers.

A Thermophile-Fermented Compost Modulates Intestinal Cations and the Expression of a Juvenile Hormone-Binding Protein Gene in the Female Larvae of Hercules Beetle Dynastes hercules (Coleoptera: Scarabaeidae)

The Hercules beetle larvae grow by feeding on humus, and adding a thermophile-fermented compost to the humus can upregulate the growth of female larvae. In this study, the effects of compost on the intestinal environment, including pH, cation concentrations, and organic acid concentrations of intestinal fluids, were investigated, and the RNA profile of the fat body was determined. Although the total intestinal potassium ions were similar between the larvae grown without compost (control larvae) and those with compost (compost larvae), the proportion of potassium ions in the midgut of the compost larvae drastically increased. In the midgut, an unidentified organic acid was the most abundant, and its concentration increased in the compost larvae. Transcriptome analysis showed that a gene encoding hemolymph juvenile-binding protein (JHBP) was expressed in the compost female larvae and not in the control female larvae. Expression of many genes involved in the defensive system was decreased in the compost female larvae. These results suggest that the female-specific enhancement of larval growth by compost was associated with the increased JHBP expression under conditions in which the availability of nutrition from the humus was improved by an increase in potassium ions in the midgut.

Bayesian network highlights the contributing factors for efficient arsenic phytoextraction by Pteris vittata in a contaminated field

Phytoextraction is a low-cost and eco-friendly method for removing pollutants, such as arsenic (As), from contaminated soil. One of the most studied As hyperaccumulators for soil remediation include Pteris vittata. Although phytoextraction using plant-assisted microbes has been considered a promising soil remediation method, microbial harnessing has not been achieved due to the complex and difficult to understand interactions between microbes and plants. This problem can possibly be addressed with a multi-omics approach using a Bayesian network. However, limited studies have used Bayesian networks to analyze plant-microbe interactions. Therefore, to understand this complex interaction and to facilitate efficient As phytoextraction using microbial inoculants, we conducted field cultivation experiments at two sites with different total As contents (62 and 8.9 mg/kg). Metabolome and microbiome data were obtained from rhizosphere soil samples using nuclear magnetic resonance and high-throughput sequencing, respectively, and a Bayesian network was applied to the obtained multi-omics data. In a highly As-contaminated site, inoculation with Pseudomonas sp. strain m307, which is an arsenite-oxidizing microbe having multiple copies of the arsenite oxidase gene, increased As concentration in the shoots of P. vittata to 157.5 mg/kg under this treatment; this was 1.5-fold higher than that of the other treatments. Bayesian network demonstrated that strain m307 contributed to As accumulation in P. vittata. Furthermore, the network showed that microbes belonging to the MND1 order positively contributed to As accumulation in P. vittata. Based on the ecological characteristics of MND1, it was suggested that the rhizosphere of P. vittata inoculated with strain m307 was under low-nitrogen conditions. Strain m307 may have induced low-nitrogen conditions via arsenite oxidation accompanied by nitrate reduction, potentially resulting in microbial iron reduction or the prevention of microbial iron oxidation. These conditions may have enhanced the bioavailability of arsenate, leading to increased As accumulation in P. vittata.

Patterns of bacterial distance decay and community assembly in different land-use types as influenced by tillage management and soil layers

Land use and cover change are major factors driving global change and greatly impact terrestrial organisms, especially soil microbial diversity. Little is known, however, about bacterial diversity, distribution patterns and assembly processes across different land use types. In this study, therefore, we conducted a large-scale field survey of 48 sampling sites, encompassing different land use types in Xuancheng city, China, with different degrees of soil disturbance and different soil horizons. The distance-decay relationships (DDRs), assembly processes and the spatial patterns of soil bacterial communities were investigated based on high-throughput sequencing data. We found that the DDRs might be weakened by anthropogenic disturbances, which were not observed in tilled soils, while a decreasing trend was observed along the soil horizon in untilled soils. The relative importance of environmental factors and geographic distance varied with soil tillage. Specifically, bacterial communities in tilled soils were driven by non-spatially autocorrelated environmental factors, while untilled soils were more susceptible to geographic distance. In addition, the heterogeneity of soil properties, as well as the differences in soil bacterial niche width and niche overlap, determined the assembly processes of the bacterial community, resulting in opposite trends along the soil layers in tilled and untilled soils. These findings expand the current understanding of the biogeography of soil bacterial communities across different land use types.

Estimation of silent phenotypes of calf antibiotic dysbiosis

Reducing antibiotic usage among livestock animals to prevent antimicrobial resistance has become an urgent issue worldwide. This study evaluated the effects of administering chlortetracycline (CTC), a versatile antibacterial agent, on the performance, blood components, fecal microbiota, and organic acid concentrations of calves. Japanese Black calves were fed with milk replacers containing CTC at 10 g/kg (CON group) or 0 g/kg (EXP group). Growth performance was not affected by CTC administration. However, CTC administration altered the correlation between fecal organic acids and bacterial genera. Machine learning (ML) methods such as association analysis, linear discriminant analysis, and energy landscape analysis revealed that CTC administration affected populations of various types of fecal bacteria. Interestingly, the abundance of several methane-producing bacteria at 60 days of age was high in the CON group, and the abundance of Lachnospiraceae, a butyrate-producing bacterium, was high in the EXP group. Furthermore, statistical causal inference based on ML data estimated that CTC treatment affected the entire intestinal environment, potentially suppressing butyrate production, which may be attributed to methanogens in feces. Thus, these observations highlight the multiple harmful impacts of antibiotics on the intestinal health of calves and the potential production of greenhouse gases by calves.

An agroecological structure model of compost-soil-plant interactions for sustainable organic farming

Compost is used worldwide as a soil conditioner for crops, but its functions have still been explored. Here, the omics profiles of carrots were investigated, as a root vegetable plant model, in a field amended with compost fermented with thermophilic Bacillaceae for growth and quality indices. Exposure to compost significantly increased the productivity, antioxidant activity, color, and taste of the carrot root and altered the soil bacterial composition with the levels of characteristic metabolites of the leaf, root, and soil. Based on the data, structural equation modeling (SEM) estimated that amino acids, antioxidant activity, flavonoids and/or carotenoids in plants were optimally linked by exposure to compost. The SEM of the soil estimated that the genus Paenibacillus and nitrogen compounds were optimally involved during exposure. These estimates did not show a contradiction between the whole genomic analysis of compost-derived Paenibacillus isolates and the bioactivity data, inferring the presence of a complex cascade of plant growth-promoting effects and modulation of the nitrogen cycle by the compost itself. These observations have provided information on the qualitative indicators of compost in complex soil-plant interactions and offer a new perspective for chemically independent sustainable agriculture through the efficient use of natural nitrogen.

Nitrogen transformation promotes the anaerobic degradation of PAHs in water level fluctuation zone of the Three Gorges Reservoir in Yangtze River, China: Evidences derived from in-situ experiment

Polycyclic aromatic hydrocarbons (PAHs) pose a great threat to human health and ecological system safety. The interception of nitrogen is common found in the riparian zone. However, there is no evidence on how nitrogen addition affects the anaerobic degradation of PAHs in soil of the water-level-fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) in Yangtze River, China. Here, we investigated the PAHs degradation rate, the variation of key functional genes and microbial communities after nitrogen addition in soil that experienced a flooding period of water-level-fluctuation. The results revealed that the ∑16PAHs were decreased 16.19 %-36.65 % and more 3-5-rings PAHs were biodegraded with nitrogen addition in WLFZ. The most genes involved in PAHs-anaerobic degradation and denitrification were up-regulated by nitrate addition, and phyla Firmicutes, Actinobacteria and Proteobacteria were more advantages in nitrogen addition groups. The Tax4Fun based genome function analysis revealed that the microbial activity of PAHs-degradation increased with nitrate addition. The co-occurrence network analysis indicated that nitrogen addition accelerated the metabolism of nitrogen and PAHs. It is the first time to provide the direct experimental evidences that nitrogen transformation in the WLFZ soil promotes anaerobic PAHs degradation. This work is of importance to understand the effect of nitrogen intercepted in the WLFZ soil of TGR in Yangtze River, China.

The research progress, hotspots, challenges and outlooks of solid-phase denitrification process

Nitrogen pollution is one of the main reasons for water eutrophication. The difficulty of nitrogen removal in low-carbon wastewater poses a huge potential threat to the ecological environment and human health. As a clean biological nitrogen removal process, solid-phase denitrification (SPD) was proposed for long-term operation of low-carbon wastewater. In this paper, the progress, hotspots, and challenges of the SPD process based on different solid carbon sources (SCSs) are reviewed. Compared with synthetic SCS and natural SCS, blended SCSs have more application potential and have achieved pilot-scale application. Differences in SCSs will lead to changes in the enrichment of hydrolytic microorganisms and hydrolytic genes, which indirectly affect denitrification performance. Moreover, the denitrification performance of the SPD process is also affected by the physical and chemical properties of SCSs, pH of wastewater, hydraulic retention time, filling ratio, and temperature. In addition, the strengthening of the SPD process is an inevitable trend. The strengthening measures including SCSs modification and coupled electrochemical technology are regarded as the current research hotspots. It is worth noting that the outbreak of the COVID-19 epidemic has led to the increase of disinfection by-products and antibiotics in wastewater, which makes the SPD process face challenges. Finally, this review proposes prospects to provide a theoretical basis for promoting the efficient application of the SPD process and coping with the challenge of the COVID-19 epidemic.

An evaluation of homeostatic plasticity for ecosystems using an analytical data science approach

The natural world is constantly changing, and planetary boundaries are issuing severe warnings about biodiversity and cycles of carbon, nitrogen, and phosphorus. In other views, social problems such as global warming and food shortages are spreading to various fields. These seemingly unrelated issues are closely related, but it can be said that understanding them in an integrated manner is still a step away. However, progress in analytical technologies has been recognized in various fields and, from a microscopic perspective, with the development of instruments including next-generation sequencers (NGS), nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC/MS), and liquid chromatography-mass spectrometry (LC/MS), various forms of molecular information such as genome data, microflora structure, metabolome, proteome, and lipidome can be obtained. The development of new technology has made it possible to obtain molecular information in a variety of forms. From a macroscopic perspective, the development of environmental analytical instruments and environmental measurement facilities such as satellites, drones, observation ships, and semiconductor censors has increased the data availability for various environmental factors. Based on these background, the role of computational science is to provide a mechanism for integrating and understanding these seemingly disparate data sets. This review describes machine learning and the need for structural equations and statistical causal inference of these data to solve these problems. In addition to introducing actual examples of how these technologies can be utilized, we will discuss how to use these technologies to implement environmentally friendly technologies in society.