MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data

High geogenic soil thallium shows limited impact on bacterial community

Thallium (Tl) is a highly toxic trace metal, included in the US EPA list of priority pollutants. Even though its toxicity is potentially higher or comparable to Cd or Hg, its environmental impact is largely unknown. Despite its toxicity, only a few recent studies are mapping the impact of recently introduced Tl on soil microbial communities, namely in agricultural systems but no studies focus on its long term effect. To complement the understanding of the impact of Tl on soil, this study aims to describe the influence of extremely high naturally occurring Tl concentration (50 mg/kg of potentially bioavailable Tl) on soil microbial communities. Our investigation concentrated on samples collected at Buus (Erzmatt, Swiss Jura, Switzerland), encompassing forest and meadow soil profiles of the local soil formed on hydrothermally mineralized dolomite rock, which is naturally rich in Tl. The soil profiles showed a significant proportion of potentially bioavailable Tl. Yet, even this high concentration of Tl has a limited impact on the richness of the soil bacterial community. Only the meadow soil samples show a reduced richness compared to control samples. Furthermore, our analysis of geogenic Tl contamination in the region unveiled a surprising finding: compared to other soils of Switzerland and in stark contrast to soils affected by recent mining activities, the structure of the bacterial community in Buus remained relatively unaffected. This observation highlights the unique ability of soil microbial communities to withstand extreme Tl contamination. Our study advances the understanding of Tl's environmental impact and underscores the resilience of soil microbes in the face of severe long-term contamination.

Soil amendments promoting nitrifying bacteria recovery faster than the denitrifying bacteria at post soil fumigation

Chloropicrin (CP) is a soil fumigant that not only reduces disease-causing pathogenic microbes but regrettably also those that benefit soil quality and crop health. However, we have few knowledge on rapidly restoring populations of beneficial microbes suppressed by CP fumigation. Here we used genetic sequencing technology to monitor changes in the recovery of soil bacteria in response to ammonium sulfate added to the soil following CP fumigation. The results showed that regardless of the N fertilizer addition rate, the accumulated NH4+-N in CP fumigated soil was rapidly consumed within 42 d. The rapid reduction in NH4+-N coincided with the observed recovery nitrogen-cycling microorganisms, especially the nitrification bacteria AOA and AOB that contributed to the formation of NH4+-N. Additionally, we further observed that the resilience index of nitrifying bacteria (AOB and AOA) was greater than the resilience index of denitrifying bacteria that contain the denitrification genes nirS, nirK and nosZ (0.12 to 0.55 vs. -0.27 to 0.073). These results revealed that N fertilizer stimulated the recovery of nitrifying bacteria more than denitrifying bacteria. Our research suggests that ammonium sulfate applied to CP fumigated soil could be used commercially to improve soil health as a result of an increase in beneficial microbes.

Probiotic consortium modulating the gut microbiota composition and function of sterile Mediterranean fruit flies

The sterile insect technique (SIT) remains a successful approach in managing pest insects. However, the long-term mass rearing and sterilizing radiation associated with SIT have been observed to induce physiological and ecological fitness decline in target insects. This decline may be attributed to various factors, including commensal microbiota dysbiosis, selection procedures, loss of heterozygosity, and other complex interactions.. There is evidence that the bacterial symbiont of insects may play critical roles in digestion, development, reproduction, and behavior. Probiotics are an increasingly common approach for restoring the intestinal microbiota structure and fitness parameters of sterile insects, particularly in the Vienna 8 genetic sexing strain (V8-GSS) of the Mediterranean fruit fly (medfly), Ceratitis capitata. Here, we explore the influence of the previously isolated bacterial strain, Lactococcus lactis, Enterobacter sp., and Klebsiella oxytoca, administration as probiotic consortia (LEK-PC) to the larvae and/or adult diet over the course of 20 rearing generations on fitness parameters. The experiment was carried out in four colonies: a control colony (C), one to which probiotics were not added, one to which probiotics were added to the larval medium (L+), one to which probiotics were added to the adult medium (A+), and one to which probiotics were added to both the larval and adult mediums (AL+). Emergence, flight ability, survival under stress conditions, and mating competitiveness, were all significantly improved by the LEK-PC treatment independently of the administration stage. The intestinal microbiota structure of various medfly V8-GSS colonies also underwent a significant shift, despite the fact that the core microbial community was unaffected by the LEK-PC administration stage, according to 16S metagenomics sequencing. Comparison of the metabolic function prediction and associated carbohydrate enzymes among colonies treated with "LEK-PC" showed an enrichment of metabolic functions related to carbohydrates, amino acids, cofactors, and vitamins metabolism, as well as, glycoside hydrolase enzymes in the AL+ colony compared to the control. This study enriches the knowledge regarding the benefits of probiotic treatment to modulate and restore the intestinal microbiota of C. capitata sterile males for a better effectiveness of the SIT.

Seed bacterial microbiota in post-submergence tolerant and sensitive barley genotypes

Flooding is a predominant abiotic stress for cultivated plants, including barley. This cereal crop shows a large adaptability to different environmental conditions, suggesting the presence of key traits to tolerate adverse conditions. During germination, genetic variations account for dissimilarities in flooding tolerance. However, differences in the seed microbiota may also contribute to tolerance/sensitivity during seedling establishment. This work investigated differences in microbiome among the grains of barley accessions. Two barley phenotypes were compared, each either tolerant or sensitive to a short submergence period followed by a recovery. The study used a metataxonomic analysis based on 16S ribosomal RNA gene sequencing and subsequent functional prediction. Our results support the hypothesis that bacterial microbiota inhabiting the barley seeds are different between sensitive and tolerant barley accessions, which harbour specific bacterial phyla and families. Finally, bacteria detected in tolerant barley accessions show a peculiar functional enrichment that suggests a possible connection with successful germination and seedling establishment.

A metagenomic comparison of clearwater, probiotic, and Rapid BFTTM on Pacific whiteleg shrimp, Litopenaeus vannamei cultures

Biofloc technology improves water quality and promote the growth of beneficial bacteria community in shrimp culture. However, little is known about the bacteria community structure in both water and gut of cultured organisms. To address this, the current study characterised the metagenomes derived from water and shrimp intestine samples of novel Rapid BFTTM with probiotic and clearwater treatments using 16S V4 region and full length 16S sequencing. Bacteria diversity of water and intestine samples of Rapid BFTTM and probiotic treatments were similar. Based on the 16S V4 region, water samples of >20 μm biofloc had the highest abundance of amplicon sequence variant (ASV). However, based on full length 16S, no clear distinction in microbial diversity was observed between water samples and intestine samples. Proteobacteria was the most abundant taxon in all samples based on both 16S V4 and full length 16S sequences. Vibrio was among the highest genus based on 16S V4 region but only full length 16S was able to discern up to species level, with three Vibrios identified-V. harveyi, V. parahaemolyticus and V. vulnificus. Vibrio harveyi being the most abundant species in all treatments. Among water samples, biofloc water samples had the lowest abundance of all three Vibrios, with V. vulnificus was present only in bioflocs of <20 μm. Predicted functional profiles of treatments support the beneficial impacts of probiotic and biofloc inclusion into shrimp culture system. This study highlights the potential displacement of opportunistic pathogens by the usage of biofloc technology (Rapid BFTTM) in shrimp culture.

Predicting variable gene content in Escherichia coli using conserved genes

Having the ability to predict the protein-encoding gene content of an incomplete genome or metagenome-assembled genome is important for a variety of bioinformatic tasks. In this study, as a proof of concept, we built machine learning classifiers for predicting variable gene content in Escherichia coli genomes using only the nucleotide k-mers from a set of 100 conserved genes as features. Protein families were used to define orthologs, and a single classifier was built for predicting the presence or absence of each protein family occurring in 10%-90% of all E. coli genomes. The resulting set of 3,259 extreme gradient boosting classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across multi-locus sequence types and that the trend can be recapitulated by sampling a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including "hypothetical proteins" was accurately predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions had slightly lower F1 scores but were still accurate (F1s = 0.895, 0.872, 0.824, and 0.841 for transposon, phage, plasmid, and antimicrobial resistance-related functions, respectively). Finally, using a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources, we observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data. IMPORTANCE Having the ability to predict the protein-encoding gene content of a genome is important for assessing genome quality, binning genomes from shotgun metagenomic assemblies, and assessing risk due to the presence of antimicrobial resistance and other virulence genes. In this study, we built a set of binary classifiers for predicting the presence or absence of variable genes occurring in 10%-90% of all publicly available E. coli genomes. Overall, the results show that a large portion of the E. coli variable gene content can be predicted with high accuracy, including genes with functions relating to horizontal gene transfer. This study offers a strategy for predicting gene content using limited input sequence data.

ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization

SUMMARY

Microbiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, for analyzing functional profiles derived from 16S rRNA sequencing. This powerful tool enables researchers to conduct extensive differential abundance analyses and generate visually appealing visualizations that effectively highlight functional signals. With ggpicrust2, users can obtain publishable results and gain deeper insights into the functional composition of their microbial communities.

AVAILABILITY AND IMPLEMENTATION

The package is open-source under the MIT and file license and is available at CRAN and https://github.com/cafferychen777/ggpicrust2. Its shiny web is available at https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/.

Nitrate determines the bacterial habitat specialization and impacts microbial functions in a subsurface karst cave

Karst caves are usually considered as natural laboratories to study pristine microbiomes in subsurface biosphere. However, effects of the increasingly detected nitrate in underground karst ecosystem due to the acid rain impact on microbiota and their functions in subsurface karst caves have remained largely unknown. In this study, samples of weathered rocks and sediments were collected from the Chang Cave, Hubei province and subjected to high-throughput sequencing of 16S rRNA genes. The results showed that nitrate significantly impacted bacterial compositions, interactions, and functions in different habitats. Bacterial communities clustered according to their habitats with distinguished indicator groups identified for each individual habitat. Nitrate shaped the overall bacterial communities across two habitats with a contribution of 27.2%, whereas the pH and TOC, respectively, structured bacterial communities in weathered rocks and sediments. Alpha and beta diversities of bacterial communities increased with nitrate concentration in both habitats, with nitrate directly affecting alpha diversity in sediments, but indirectly on weathered rocks by lowering pH. Nitrate impacted more on bacterial communities in weathered rocks at the genus level than in sediments because more genera significantly correlated with nitrate concentration in weathered rocks. Diverse keystone taxa involved in nitrogen cycling were identified in the co-occurrence networks such as nitrate reducers, ammonium-oxidizers, and N₂-fixers. Tax4Fun2 analysis further confirmed the dominance of genes involved in nitrogen cycling. Genes of methane metabolism and carbon fixation were also dominant. The dominance of dissimilatory and assimilatory nitrate reduction in nitrogen cycling substantiated nitrate impact on bacterial functions. Our results for the first time revealed the impact of nitrate on subsurface karst ecosystem in terms of bacterial compositions, interactions, and functions, providing an important reference for further deciphering the disturbance of human activities on the subsurface biosphere.

Indian sewage microbiome has unique community characteristics and potential for population-level disease predictions

Sewage wastewater pollutes water and poses a public health issue but it could also prove useful in certain research domains. Sewage is a complex niche relevant for research concerning 'one-health', human health, pollution and antibiotic resistance. Indian gut microbiome is also understudied due to sampling constraints and sewage could be used to explore it. Ostensibly, Indian sewage needs to be studied and here, we performed a cross-sectional pan-India sewage sampling to generate the first comprehensive Indian sewage microbiome. Indian sewage showed predominance of Burkholderiaceae, Rhodocyclaceae, Veillonellaceae, Prevotellaceae, etc. and has high representation of gut microbes. The identified gut microbes have overrepresentation of Veillonellaceae, Rikenellaceae, Streptococcaceae, and Bacillaceae. Imputed metagenomics of sewage microbiome indicated dominance of transport, motility, peptidases, amino acid metabolism, and antibiotic resistance genes. Microbiome-disease associations drawn using simple decision tree and random forest analysis identified specific microbes as potential predictors of diabetes and obesity in a city. Altogether, we generated the first Indian sewage microbiome and our non-invasive, high-throughput workflow could be emulated for future research, wastewater-based epidemiology and designing policies concerning public health.

Microbiome analysis revealed distinct microbial communities occupying different sized nodules in field-grown peanut

Legume nodulation is the powerhouse of biological nitrogen fixation (BNF) where host-specific rhizobia dominate the nodule microbiome. However, other rhizobial or non-rhizobial inhabitants can also colonize legume nodules, and it is unclear how these bacteria interact, compete, or combinedly function in the nodule microbiome. Under such context, to test this hypothesis, we conducted 16S-rRNA based nodule microbiome sequencing to characterize microbial communities in two distinct sized nodules from field-grown peanuts inoculated with a commercial inoculum. We found that microbial communities diverged drastically in the two types of peanut nodules (big and small). Core microbial analysis revealed that the big nodules were inhabited by Bradyrhizobium, which dominated composition (>99%) throughout the plant life cycle. Surprisingly, we observed that in addition to Bradyrhizobium, the small nodules harbored a diverse set of bacteria (~31%) that were not present in big nodules. Notably, these initially less dominant bacteria gradually dominated in small nodules during the later plant growth phases, which suggested that native microbial communities competed with the commercial inoculum in the small nodules only. Conversely, negligible or no competition was observed in the big nodules. Based on the prediction of KEGG pathway analysis for N and P cycling genes and the presence of diverse genera in the small nodules, we foresee great potential of future studies of these microbial communities which may be crucial for peanut growth and development and/or protecting host plants from various biotic and abiotic stresses.

Microbiome Analysis of Traditional Grain Vinegar Produced under Different Fermentation Conditions in Various Regions in Korea

The fermentation of traditional vinegar is a spontaneous and complex process that involves interactions among various microorganisms. Here, we used a microbiome approach to determine the effects of networks, such as fermentation temperature, location, physicochemical and sensory characteristics, and bacterial profile, within traditional grain vinegar samples collected from various regions of Korea. Acetic acid and lactic acid were identified as the major metabolites of grain vinegar, and sourness and umami were determined as taste fingerprints that could distinguish between vinegar samples. Acetobacter ghanensis and Lactobacillus acetotolerans were the predominant bacterial species, and the functional composition of the microbiota revealed that the nucleotide biosynthesis pathway was the most enriched. These results reveal that vinegar samples fermented outdoors are more similar to each other than vinegar samples fermented at 30 °C, when comparing the distance matrix for comprehending bacterial networks among samples. This study may help obtain high-quality vinegar through optimized fermentation conditions by suggesting differences in sensory characteristics according to the fermentation environment.

Prospects of advanced metagenomics and meta-omics in the investigation of phytomicrobiome to forecast beneficial and pathogenic response

Microorganisms dwell in diverse plant niches as non-axenic biotic components that are beneficial as well pathogenic for the host. They improve nutrients-uptake, stress tolerance, phytohormone synthesis, and strengthening the defense system through phyllosphere, rhizosphere, and endosphere. The negative consequences of the microbial communities are largely in the form of diseases characterized by certain symptoms such as gall, cankers, rots etc. Uncultivable and unspecified nature of different phytomicrobiomes communities is a challenge in the management of plant disease, a leading cause for the loss of the plant products. Metagenomics has opened a new gateway for the exploration of microorganisms that are hitherto unknown, enables investigation of the functional aspect of microbial gene products through metatranscriptomics and metabolomics. Metagenomics offers advantages of characterizing previously unknown microorganisms from extreme environments like hot springs, glaciers, deep seas, animal gut etc. besides bioprospecting gene products such as Taq polymerase, bor encoded indolotryptoline, hydrolases, and polyketides. This review provides a detailed account of the phytomicrobiome networks and highlights the importance and limitations of metagenomics and other meta-omics approaches for the understanding of plant microbial diversity with special focus on the disease control and its management.

Metagenomic Insights into the Gut Microbiota of Eudrilus eugeniae (Kinberg) and Its Potential Roles in Agroecosystem

Gut microbiomes, a consortium of microorganisms that live in the animal gut, are highly engineered microbial communities. It makes a major contribution to digestive health, metabolism management, and the development of a strong immune system in the host. The present study was taken up to answer the long-running question about the existence of truly indigenous microflora of the epigeic earthworm gut. This is due to the general difficulties of culturing many of the microorganisms found in soil or earthworms' gut. Keeping this fact in a view, the metagenomics approach using 16S rRNA marker gene incorporated with amplicon-based sequencing was used to explore microbiota of commercially overriding, diversely fed epigeic earthworm Eudrilus eugeniae (Kinberg) in three varied habitats viz., artificial soil (AS), organic agricultural farm soil (OAFS) and conventional agriculture farm soil (CAFS). There are predominant bacteria that belong to different phyla such as Proteobacteria (29.72-76.81%), Actinobacteria (11.06-34.42%), Firmicutes (6.02-19.81%), and Bacteroidetes (2.40-9.22%) present in the gut of E. eugeniae. The alpha diversity (Observed species, Chao1, ACE, Shannon, Simpson, and Fisher alpha) indices showed that OAFS had significantly higher alpha diversity than AS and CAFS groups. The core microbiota analysis showed that OAFS and AS groups had a relatively similar bacterial panel in comparison to the CAFS group. Various statistical tools i.e. MetagenomeSeq, LEfSe, and Random Forest analysis were performed and the findings demonstrated prevalence of the most significant bacterial genera; Aeromonas, Gaiella, and Burkholderia in CAFS group. Nonetheless, in AS and OAFS groups, the common existence of Anaerosporobacter and Aquihabitans were found respectively. Metagenomic functional prediction revealed that earthworms' gut microbial communities were actively involved in multiple organic and xenobiotics compound degradation-related pathways. This is the first research to use high-throughput 16S rRNA gene amplicon sequencing to show the gut microbiota of E. eugeniae in diverse agricultural systems. The findings suggest the configuration of the gut microbiota of earthworms and its potential role in the soil ecosystem depends on the microbial communities of the soil.

Bacterial Endophytes Contribute to Rice Seedling Establishment Under Submergence

Flooding events caused by severe rains and poor soil drainage can interfere with plant germination and seedling establishment. Rice is one of the cereal crops that has unique germination strategies under flooding. One of these strategies is based on the fast coleoptile elongation in order to reach the water surface and re-establish the contact with the air. Microorganisms can contribute to plant health via plant growth promoters and provide protection from abiotic stresses. To characterise the community composition of the microbiome in rice germination under submergence, a 16S rRNA gene profiling metagenomic analysis was performed of temperate japonica rice varieties Arborio and Lamone seedlings, which showed contrasting responses in terms of coleoptile length when submerged. This analysis showed a distinct microbiota composition of Arborio seeds under submergence, which are characterised by the development of a long coleoptile. To examine the potential function of microbial communities under submergence, culturable bacteria were isolated, identified and tested for plant growth-promoting activities. A subgroup of isolated bacteria showed the capacity to hydrolyse starch and produce indole-related compounds under hypoxia. Selected bacteria were inoculated in seeds to evaluate their effect on rice under submergence, showing a response that is dependent on the rice genotype. Our findings suggest that endophytic bacteria possess plant growth-promoting activities that can substantially contribute to rice seedling establishment under submergence.

Microbiome Analysis via OTU and ASV-Based Pipelines—A Comparative Interpretation of Ecological Data in WWTP Systems

Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.