Parallel-META 3: Comprehensive taxonomical and functional analysis platform for efficient comparison of microbial communities

Acute nitrite exposure causes gut microbiota dysbacteriosis and proliferation of pathogenic Photobacterium in shrimp

Nitrite exposure has become a significant concern in the aquaculture industry, posing a severe threat to aquatic animals such as shrimp. While studies have reported the adverse effects of nitrite on shrimp growth, the part played by the gut microbiota in shrimp mortality resulting from nitrite exposure is poorly understood. Here, the effects of nitrite on shrimp gut bacterial community were investigated using 16S rRNA amplicon sequencing, bacterial isolation, genomic analysis, and infection experiments. Compared to the control_healthy group, changes in the bacterial composition of the nitrite_dead group were associated with reduced abundance of specific beneficial bacteria and increased abundance of certain pathogenic bacteria. Notably, members of the Photobacterium genus were found to be significantly enriched in the nitrite_dead group. Genomic analysis of a representative Photobacterium strain (LvS-8n3) revealed a variety of genes encoding bacterial toxins, including hemolysin, adhesin, and phospholipase. Furthermore, it was also found that LvS-8n3 exhibits strong pathogenicity, probably due to its high production of pathogenic factors and the ability to utilize nitrite for proliferation. Therefore, the proliferation of pathogenic Photobacterium species appears pivotal for driving shrimp mortality caused by nitrite exposure. These findings provide novel insights into the disease mechanism in shrimp under conditions of environmental change.

Extremely halophilic brine community manipulation shows higher robustness of microbiomes inhabiting human-driven solar saltern than naturally driven lake

Hypersaline ecosystems display taxonomically similar assemblages with low diversities and highly dense accompanying viromes. The ecological implications of viral infection on natural microbial populations remain poorly understood, especially at finer scales of diversity. Here, we sought to investigate the influence of changes in environmental physicochemical conditions and viral predation pressure by autochthonous and allochthonous viruses on host dynamics. For this purpose, we transplanted two microbiomes coming from distant hypersaline systems (solar salterns of Es Trenc in Spain and the thalassohaline lake of Aran-Bidgol lake in Iran), by exchanging the cellular fractions with the sterile-filtered accompanying brines with and without the free extracellular virus fraction. The midterm exposure (1 month) of the microbiomes to the new conditions showed that at the supraspecific taxonomic range, the assemblies from the solar saltern brine more strongly resisted the environmental changes and viral predation than that of the lake. The metagenome-assembled genomes (MAGs) analysis revealed an intraspecific transition at the ecotype level, mainly driven by changes in viral predation pressure, by both autochthonous and allochthonous viruses.

IMPORTANCE

Viruses greatly influence succession and diversification of their hosts, yet the effects of viral infection on the ecological dynamics of natural microbial populations remain poorly understood, especially at finer scales of diversity. By manipulating the viral predation pressure by autochthonous and allochthonous viruses, we uncovered potential phage-host interaction, and their important role in structuring the prokaryote community at an ecotype level.

16S rRNA female reproductive microbiome investigation reveals Dalfopristin, Clorgyline, and Hydrazine as potential therapeutics for the treatment of bacterial vaginosis

Bacterial vaginosis (BV) is a prevalent vaginal illness resulting from a disruption in the vaginal microbial equilibrium. The vaginal microbiota has been shown to have a substantial impact on the development and continuation of BV. This work utilized 16S rRNA sequence analysis of vaginal microbiome samples (Control vs BV samples) utilizing Parallel-Meta 3 to investigate the variations in microbial composition. The unique genes identified were used to determine prospective therapeutic targets and their corresponding inhibitory ligands. Further, molecular docking was conducted and then MD simulations were carried out to confirm the docking outcomes. In the BV samples, we detected several anaerobic bacteria recognized for their ability to generate biofilms, namely Acetohalobium, Anaerolineaceae, Desulfobacteraceae, and others. Furthermore, we identified Dalfopristin, Clorgyline, and Hydrazine as potential therapeutic options for the management of BV. This research provides new insights into the causes of BV and shows the potential effectiveness of novel pharmacological treatments.

Biomarker Identification for Preterm Birth Susceptibility: Vaginal Microbiome Meta-Analysis Using Systems Biology and Machine Learning Approaches

PROBLEM

The vaginal microbiome has a substantial role in the occurrence of preterm birth (PTB), which contributes substantially to neonatal mortality worldwide. However, current bioinformatics approaches mostly concentrate on the taxonomic classification and functional profiling of the microbiome, limiting their abilities to elucidate the complex factors that contribute to PTB.

METHOD OF STUDY

A total of 3757 vaginal microbiome 16S rRNA samples were obtained from five publicly available datasets. The samples were divided into two categories based on pregnancy outcome: preterm birth (PTB) (N = 966) and term birth (N = 2791). Additionally, the samples were further categorized based on the participants' race and trimester. The 16S rRNA reads were subjected to taxonomic classification and functional profiling using the Parallel-META 3 software in Ubuntu environment. The obtained abundances were analyzed using an integrated systems biology and machine learning approach to determine the key microbes, pathways, and genes that contribute to PTB. The resulting features were further subjected to statistical analysis to identify the top nine features with the greatest effect sizes.

RESULTS

We identified nine significant features, namely Shuttleworthia, Megasphaera, Sneathia, proximal tubule bicarbonate reclamation pathway, systemic lupus erythematosus pathway, transcription machinery pathway, lepA gene, pepX gene, and rpoD gene. Their abundance variations were observed through the trimesters.

CONCLUSIONS

Vaginal infections caused by Shuttleworthia, Megasphaera, and Sneathia and altered small metabolite biosynthesis pathways such as lipopolysaccharide folate and retinal may increase the susceptibility to PTB. The identified organisms, genes, pathways, and their networks may be specifically targeted for the treatment of bacterial infections that increase PTB risk.

Airborne antibiotic resistome and microbiome in pharmaceutical factories

Antimicrobial resistance is considered to be one of the biggest public health problems, and airborne transmission is an important but under-appreciated pathway for the spread of antibiotic resistance genes (ARGs) in the environment. Previous research has shown pharmaceutical factories to be a major source of ARGs and antibiotic resistant bacteria (ARB) in the surrounding receiving water and soil environments. Pharmaceutical factories are hotspots of antibiotic resistance, but the atmospheric transmission and its environmental risk remain more concerns. Here, we conducted a metagenomic investigation into the airborne microbiome and resistome in three pharmaceutical factories in China. Soil (average: 38.45%) and wastewater (average: 28.53%) were major contributors of airborne resistome. ARGs (vanR/vanS, blaOXA, and CfxA) conferring resistance to critically important clinically used antibiotics were identified in the air samples. The wastewater treatment area had significantly higher relative abundances of ARGs (average: 0.64 copies/16S rRNA). Approximately 28.2% of the detected airborne ARGs were found to be associated with plasmids, and this increased to about 50% in the wastewater treatment area. We have compiled a list of high-risk airborne ARGs found in pharmaceutical factories. Moreover, A total of 1,043 viral operational taxonomic units were identified and linked to 47 family-group taxa. Different CRISPR-Cas immune systems have been identified in bacterial hosts in response to phage infection. Similarly, higher phage abundance (average: 2451.70 PPM) was found in the air of the wastewater treatment area. Our data provide insights into the antibiotic resistance gene profiles and microbiome (bacterial and non-bacterial) in pharmaceutical factories and reveal the potential role of horizontal transfer in the spread of airborne ARGs, with implications for human and animal health.

Diversity of the Maize Root Endosphere and Rhizosphere Microbiomes Modulated by the Inoculation with Pseudomonas fluorescens UM270 in a Milpa System

Milpa is an agroecological production system based on the polyculture of plant species, with corn featuring as a central component. Traditionally, the milpa system does not require the application of chemicals, and so pest attacks and poor growth in poor soils can have adverse effects on its production. Therefore, the application of bioinoculants could be a strategy for improving crop growth and health; however, the effect of external inoculant agents on the endemic microbiota associated with corn has not been extensively studied. Here, the objective of this work was to fertilize a maize crop under a milpa agrosystem with the PGPR Pseudomonas fluorescens UM270, evaluating its impact on the diversity of the rhizosphere (rhizobiome) and root endophytic (root endobiome) microbiomes of maize plants. The endobiome of maize roots was evaluated by 16S rRNA and internal transcribed spacer region (ITS) sequencing, and the rhizobiome was assessed by metagenomic sequencing upon inoculation with the strain UM270. The results showed that UM270 inoculation of the rhizosphere of P. fluorescens UM270 did not increase alpha diversity in either the monoculture or milpa, but it did alter the endophytic microbiome of maize plant roots by stimulating the presence of bacterial operational taxonomic units (OTUs) of the genera Burkholderia and Pseudomonas (in a monoculture), whereas, in the milpa system, the PGPR stimulated greater endophytic diversity and the presence of genera such as Burkholderia, Variovorax, and N-fixing rhizobia genera, including Rhizobium, Mesorhizobium, and Bradyrhizobium. No clear association was found between fungal diversity and the presence of strain UM270, but beneficial fungi, such as Rizophagus irregularis and Exophiala pisciphila, were detected in the Milpa system. In addition, network analysis revealed unique interactions with species such as Stenotrophomonas sp., Burkholderia xenovorans, and Sphingobium yanoikuyae, which could potentially play beneficial roles in the plant. Finally, the UM270 strain does not seem to have a strong impact on the microbial diversity of the rhizosphere, but it does have a strong impact on some functions, such as trehalose synthesis, ammonium assimilation, and polyamine metabolism. The inoculation of UM270 biofertilizer in maize plants modifies the rhizo- and endophytic microbiomes with a high potential for stimulating plant growth and health in agroecological crop models.

Acute Ammonia Causes Pathogenic Dysbiosis of Shrimp Gut Biofilms

Acute ammonia exposure has detrimental effects on shrimp, but the underlying mechanisms remain to be fully explored. In the present study, we investigated the impact of acute ammonia exposure on the gut microbiota of the white shrimp Litopenaeus vannamei and its association with shrimp mortality. Exposure to a lethal concentration of ammonia for 48 h resulted in increased mortality in L. vannamei, with severe damage to the hepatopancreas. Ammonia exposure led to a significant decrease in gut microbial diversity, along with the loss of beneficial bacterial taxa and the proliferation of pathogenic Vibrio strains. A phenotypic analysis revealed a transition from the dominance of aerobic to facultative anaerobic strains due to ammonia exposure. A functional analysis revealed that ammonia exposure led to an enrichment of genes related to biofilm formation, host colonization, and virulence pathogenicity. A species-level analysis and experiments suggest the key role of a Vibrio harveyi strain in causing shrimp disease and specificity under distinct environments. These findings provide new information on the mechanism of shrimp disease under environmental changes.

Metagenomic analysis revealed the potential of lactic acid bacteria in improving natural saline-alkali land

Management and improving saline-alkali land is necessary for sustainable agricultural development. We conducted a field experiment to investigate the effects of spraying lactic acid bacteria (LAB) on the cucumber and tomato plant soils. Three treatments were designed, including spraying of water, viable or sterilized LAB preparations to the soils of cucumber and tomato plants every 20 days. Spraying sterilized or viable LAB could reduce the soil pH, with a more obvious effect by using viable LAB, particularly after multiple applications. Metagenomic sequencing revealed that the soil microbiota in LAB-treated groups had higher alpha-diversity and more nitrogen-fixing bacteria compared with the water-treated groups. Both viable and sterilized LAB, but not water application, increased the complexity of the soil microbiota interactive network. The LAB-treated subgroups were enriched in some KEGG pathways compared with water or sterilized LAB subgroups, such as environmental information processing-related pathways in cucumber plant; and metabolism-related pathways in tomato plant, respectively. Redundancy analysis revealed association between some soil physico-chemical parameters (namely soil pH and total nitrogen) and bacterial biomarkers (namely Rhodocyclaceae, Pseudomonadaceae, Gemmatimonadaceae, and Nitrosomonadales). Our study demonstrated that LAB is a suitable strategy for decreasing soil pH and improving the microbial communities in saline-alkali land.

Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites

Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.

Microbial signatures of neonatal bacterial meningitis from multiple body sites

As a common central nervous system infection in newborns, neonatal bacterial meningitis (NBM) can seriously affect their health and growth. However, although metagenomic approaches are being applied in clinical diagnostic practice, there are some limitations for whole metagenome sequencing and amplicon sequencing in handling low microbial biomass samples. Through a newly developed ultra-sensitive metagenomic sequencing method named 2bRAD-M, we investigated the microbial signatures of central nervous system infections in neonates admitted to the neonatal intensive care unit. Particularly, we recruited a total of 23 neonates suspected of having NBM and collected their blood, cerebrospinal fluid, and skin samples for 2bRAD-M sequencing. Then we developed a novel decontamination method (Reads Level Decontamination, RLD) for 2bRAD-M by which we efficiently denoised the sequencing data and found some potential biomarkers that have significantly different relative abundance between 12 patients that were diagnosed as NBM and 11 Non-NBM based on their cerebrospinal fluid (CSF) examination results. Specifically, we discovered 11 and 8 potential biomarkers for NBM in blood and CSF separately and further identified 16 and 35 microbial species that highly correlated with the physiological indicators in blood and CSF. Our study not only provide microbiological evidence to aid in the diagnosis of NBM but also demonstrated the application of an ultra-sensitive metagenomic sequencing method in pathogenesis study.

Comparative Microbiome Analysis of Three Epidemiologically Important Tick Species in Latvia

(1) Background: Amplicon-based 16S rRNA profiling is widely used to study whole communities of prokaryotes in many niches. Here, we comparatively examined the microbial composition of three tick species, Ixodes ricinus, Ixodes persulcatus and Dermacentor reticulatus, which were field-collected in Latvia. (2) Methods: Tick DNA samples were used for microbiome analysis targeting bacterial 16S rDNA using next-generation sequencing (NGS). (3) Results: The results showed significant differences in microbial species diversity and composition by tick species and life stage. A close similarity between microbiomes of I. ricinus and I. persulcatus ticks was observed, while the D. reticulatus microbiome composition appeared to be more distinct. Significant differences in alpha and beta microbial diversity were observed between Ixodes tick life stages and sexes, with lower taxa richness indexes obtained for female ticks. The Francisella genus was closely associated with D. reticulatus ticks, while endosymbionts Candidatus Midichlorii and Candidatus Lariskella were associated with I. ricinus and I. persulcatus females, respectively. In I. ricinus females, the endosymbiont load negatively correlated with the presence of the Rickettsia genus. (4) Conclusions: The results of this study revealed important associations between ticks and their microbial community and highlighted the microbiome features of three tick species in Latvia.

Mariculture affects antibiotic resistome and microbiome in the coastal environment

Antibiotics are increasingly used and released into the marine environment due to the rapid development of mariculture, resulting in spread of antibiotic resistance. The pollution, distribution, and characteristics of antibiotics, antibiotic resistance genes (ARGs) and microbiomes have been investigated in this study. Results showed that 20 antibiotics were detected in Chinese coastal environment, with predominance of erythromycin-H₂O, enrofloxacin and oxytetracycline. In coastal mariculture sites, antibiotic concentrations were significantly higher than in control sites, and more types of antibiotics were detected in the South than in the North of China. Residues of enrofloxacin, ciprofloxacin and sulfadiazine posed high resistance selection risks. β-Lactam, multi-drug and tetracycline resistance genes were frequently detected with significantly higher abundance in the mariculture sites. Of the 262 detected ARGs, 10, 26, and 19 were ranked as high-risk, current-risk, future-risk, respectively. The main bacterial phyla were Proteobacteria and Bacteroidetes, of which 25 genera were zoonotic pathogens, with Arcobacter and Vibrio in particular ranking in the top10. Opportunistic pathogens were more widely distributed in the northern mariculture sites. Phyla of Proteobacteria and Bacteroidetes were the potential hosts of high-risk ARGs, while the conditional pathogens were associated with future-risk ARGs, indicating a potential threat to human health.

A bacterial symbiont in the gill of the marine scallop Argopecten irradians irradians metabolizes dimethylsulfoniopropionate

Microbial lysis of dimethylsulfoniopropionate (DMSP) is a key step in marine organic sulfur cycling and has been recently demonstrated to play an important role in mediating interactions between bacteria, algae, and zooplankton. To date, microbes that have been found to lyse DMSP are largely confined to free-living and surface-attached bacteria. In this study, we report for the first time that a symbiont (termed "Rhodobiaceae bacterium HWgs001") in the gill of the marine scallop Argopecten irradians irradians can lyse and metabolize DMSP. Analysis of 16S rRNA gene sequences suggested that HWgs001 accounted for up to 93% of the gill microbiota. Microscopic observations suggested that HWgs001 lived within the gill tissue. Unlike symbionts of other bivalves, HWgs001 belongs to Alphaproteobacteria rather than Gammaproteobacteria, and no genes for carbon fixation were identified in its small genome. Moreover, HWgs001 was found to possess a dddP gene, responsible for the lysis of DMSP to acrylate. The enzymatic activity of dddP was confirmed using the heterologous expression, and in situ transcription of the gene in scallop gill tissues was demonstrated using reverse-transcription PCR. Together, these results revealed a taxonomically and functionally unique symbiont, which represents the first-documented DMSP-metabolizing symbiont likely to play significant roles in coastal marine ecosystems.

Effects of dietary supplementation of probiotic and Spirulina platensis microalgae powder on growth performance immune response, carcass characteristics, gastrointestinal microflora and meat quality in broilers chick

BACKGROUND

With the potential development of human pathogenic bacteria resistant to antibiotics, the use of antibiotics as growth promoter in poultry production was banned in different countries, and it has forced the poultry industry to consider 'Biologically safer' alternatives to antibiotics, among which the probiotics and microalgae can be mentioned.

OBJECTIVE

Present study aimed to compare Spirulina platensis microalgae in combination with a native probiotic as an alternative to antibiotics.

METHODS

336 male broiler chicks were allotted into 7 treatments and 4 repetitions in a completely randomised design to evaluate chick's performance and immune response to different treatment based on indexes as feed intake, weight gain, feed conversion ratio, humoral immunity, carcass characteristics, thigh and breast pH, intestinal morphology and microbial population. European production efficiency coefficient was also reported.

RESULTS

No significant difference was appeared in the pH of thigh and breast meat (p > 0.05). Supplementation of diets with SP_0.3 revealed better villi height, villi length to crypt depth ratio and villi surface. With significant difference (p < 0.05), the highest and lowest colonies of Lactobacillus and E. coli were recorded for PR_0.5 SP_0.3 treatments.

CONCLUSIONS

Supplementation of broilers diets either with probiotic prepared from the microorganism isolated of native birds (1 g/kg) or S. platensis (0.2 g/kg) alone and their combination (0.3 g/kg of S. platensis in combination with 0.5 g/kg of native probiotic) are promising and can be a good alternative to antibiotics, lead to progress of broiler's performance.

Construction of a caries diagnosis model based on microbiome novelty score

OBJECTIVES

This study aimed to analyze the bacteria in dental caries and establish an optimized dental-ca-ries diagnosis model based on 16S ribosomal RNA (rRNA) data of oral flora.

METHODS

We searched the public databa-ses of microbiomes including NCBI, MG-RAST, EMBL-EBI, and QIITA and collected data involved in the relevant research on human oral microbiomes worldwide. The samples in the caries dataset (1 703) were compared with healthy ones (20 540) by using the microbial search engine (MSE) to obtain the microbiome novelty score (MNS) and construct a caries diagnosis model based on this index. Nonparametric multivariate ANOVA was used to analyze and compare the impact of different host factors on the oral flora MNS, and the model was optimized by controlling related factors. Finally, the effect of the model was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

1) The oral microbiota distribution obviously differed among people with various oral-health statuses, and the species richness and species diversity index decreased. 2) ROC curve was used to evaluate the caries data set, and the area under ROC curve was AUC=0.67. 3) Among the five hosts' factors including caries status, country, age, decayed missing filled tooth (DMFT) indices, and sampling site displayed the strongest effect on MNS of samples (P=0.001). 4) The AUC of the model was 0.87, 0.74, 0.74, and 0.75 in high caries, medium caries, low caries samples in Chinese children, and mixed dental plaque samples after controlling host factors, respectively.

CONCLUSIONS

The model based on the analysis of 16S rRNA data of oral flora had good diagnostic efficiency.

Change in the Gut Microbiome and Immunity by Lacticaseibacillus rhamnosus Probio-M9

With the exploding growth of the global market for probiotics and the rapid awakening of public awareness to manage health by probiotic intervention, there is still an active debate about whether the consumption of probiotics is beneficial for nonpatients, which is due to the lack of systematic analysis based on time series multiomics data sets. In this study, we recruited 100 adults from a college in China and performed a random case-control study by using a probiotic (Lacticaseibacillus rhamnosus Probio-M9) as an intervention for 6 weeks, aiming to achieve a comprehensive evaluation and understanding of the beneficial effect of Probio-M9 consumption. By testing advanced blood immunity indicators, sequencing the gut microbiome, and profiling the gut metabolome at baseline and the end of the study, we found that although the probiotic intervention has a limited impact on the human immunity and the gut microbiome and metabolome, the associations between the immunity indicators and multiomics data were strengthened, and further analysis of the gut microbiome's genetic variations revealed inhibited generation of single nucleotide variants (SNVs) by probiotic consumption. Taken together, our findings indicated an underestimated influence of the probiotic, not on altering the microbial composition but on strengthening the association between human immunity and commensal microbes and stabilizing the genetic variations of the gut microbiome. IMPORTANCE Although the global market for probiotics is growing explosively, there is still an active debate about whether the consumption of probiotics is beneficial for nonpatients. In this study, we recruited 100 adults from a college in China and performed 6 weeks of intervention for half of the volunteers. By analyzing the time series multiomics data in this study, we found that the probiotic intervention (i) has a limited effect on human immunity or the global structure of the gut microbiome and metabolome, (ii) can largely influence the correlation of the development between multiomics data and immunity, which was not able to be discovered by conventional differential abundance analysis, and (iii) can inhibit the generation of SNVs in the gut microbiome instead of promoting it.

Airborne antibiotic resistome and human health risk in railway stations during COVID-19 pandemic

Antimicrobial resistance is recognized as one of the greatest public health concerns. It is becoming an increasingly threat during the COVID-19 pandemic due to increasing usage of antimicrobials, such as antibiotics and disinfectants, in healthcare facilities or public spaces. To explore the characteristics of airborne antibiotic resistome in public transport systems, we assessed distribution and health risks of airborne antibiotic resistome and microbiome in railway stations before and after the pandemic outbreak by culture-independent and culture-dependent metagenomic analysis. Results showed that the diversity of airborne antibiotic resistance genes (ARGs) decreased following the pandemic, while the relative abundance of core ARGs increased. A total of 159 horizontally acquired ARGs, predominantly confering resistance to macrolides and aminoglycosides, were identified in the airborne bacteria and dust samples. Meanwhile, the abundance of horizontally acquired ARGs hosted by pathogens increased during the pandemic. A bloom of clinically important antibiotic (tigecycline and meropenem) resistant bacteria was found following the pandemic outbreak. 251 high-quality metagenome-assembled genomes (MAGs) were recovered from 27 metagenomes, and 86 genera and 125 species were classified. Relative abundance of ARG-carrying MAGs, taxonomically assigned to genus of Bacillus, Pseudomonas, Acinetobacter, and Staphylococcus, was found increased during the pandemic. Bayesian source tracking estimated that human skin and anthropogenic activities were presumptive resistome sources for the public transit air. Moreover, risk assessment based on resistome and microbiome data revealed elevated airborne health risks during the pandemic.

Composition and factors influencing community structure of lactic acid bacterial in dairy products from Nyingchi Prefecture of Tibet

This study investigated the community composition of lactic acid bacteria (LAB) from yaks' milk (YM) Tibetan yellow cattle milk (TM) and their fermented products from different counties in the Nyingchi Prefecture, Tibet using Pacific Biosciences (PacBio) single-molecule real-time (SMRT) sequencing. Sequencing revealed 26 genera and 94 species from 71 dairy samples; amongst these Lactobacillus delbrueckii (36.17%), Streptococcus thermophilus (19.46%) and Lactococcus lactis (18.33%) were the predominant species. This study also identified the main factors influencing LAB community composition by comparing amongst samples from different locations, from different milk types, and from different altitudes. The LAB communities in YM and TM were more diverse than in fermented yaks' milk (FYM) and fermented Tibetan yellow cattle milk (FTM) samples. Similarly, whether milk was fermented or not accounted for differences in LAB species composition while altitude of the dairy products had very little effect. Milk source and production process were the most likely causes of drastic shifts in microbial community composition. In addition, fermented dairy products were enriched in genes responsible for secondary metabolic pathways that were potentially beneficial for health. Comprehensive descriptions of the microbiota in different dairy products from the Nyingchi Prefecture, Tibet might help elucidate evolutionary and functional relationships amongst bacterial communities in these products.

Time-scale analysis of the long-term variability of human gut microbiota characteristics in Chinese individuals

Studying the dynamics and stability of the human gut microbiota over time is important for exploring their relationship with human health and developing treatment strategies for putative microbiome-related ailments. Here, we collected stool samples from seven healthy Chinese subjects at 1-month intervals between 2016 and 2020. Sequencing and bioinformatics analyses revealed that the bacteria in the collected fecal samples fluctuated over time, and the extent of these changes increased over time. Further, the average shared proportion value obtained using Sourcetracker2 was 63.5% for samples collected from the same individual in the preceding month, and over a 3-year period, this value decreased to 40.7%. Furthermore, the proportion of different bacteria in the gut microbiota of the different subjects fluctuated to varying degrees. Therefore, our results suggested that it is important to consider the effect of time on gut microbiota composition when it is used to evaluate health. Our study opens up a new field of microbiota research, considering not just the instantaneous microbiota, but also the change of the gut microbiota over time.

Microbial Richness of Marine Biofilms Revealed by Sequencing Full-Length 16S rRNA Genes

Marine biofilms are a collective of microbes that can grow on many different surfaces immersed in marine environments. Estimating the microbial richness and specificity of a marine biofilm community is a challenging task due to the high complexity in comparison with seawater. Here, we compared the resolution of full-length 16S rRNA gene sequencing technique of a PacBio platform for microbe identification in marine biofilms with the results of partial 16S rRNA gene sequencing of traditional Illumina PE250 platform. At the same time, the microbial richness, diversity, and composition of adjacent seawater communities in the same batch of samples were analyzed. Both techniques revealed higher species richness, as reflected by the Chao1 index, in the biofilms than that in the seawater communities. Moreover, compared with Illumina sequencing, PacBio sequencing detected more specific species for biofilms and less specific species for seawater. Members of Vibrio, Arcobacter, Photobacterium, Pseudoalteromonas, and Thalassomonas were significantly enriched in the biofilms, which is consistent with the previous understanding of species adapted to a surface-associated lifestyle and validates the taxonomic analyses in the current study. To conclude, the full-length sequencing of 16S rRNA genes has probably a stronger ability to analyze more complex microbial communities, such as marine biofilms, the species richness of which has probably been under-estimated in previous studies.

Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms

Massive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large-scale datasets. In this study, we introduce Parallel-Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state-of-the-art algorithms in a user-friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full-automatic installation.

Interactions between Human Gut Microbiome Dynamics and Sub-Optimal Health Symptoms during Seafaring Expeditions

During long ocean voyages, crew members are subject to complex pressures from their living and working environment, which lead to chronic diseases-like sub-optimal health status. Although the association between dysbiotic gut microbiome and chronic diseases has been broadly reported, the correlation between the sub-optimal health status and gut microbiome remains elusive. Here, the health status of 77 crew members (20-35 years old Chinese, male) during a 135-day sea expedition was evaluated using the shotgun metagenomics of stool samples and health questionnaires taken before and after the voyage. We found five core symptoms (e.g., abnormal defecation frequency, insomnia, poor sleep quality, nausea, and overeating) in 55 out of 77 crew members suffering from sub-optimal health status, and this was termed "seafaring syndrome" (SS) in this study. Significant correlation was found between the gut microbiome and SS rather than any single symptom. For example, SS was proven to be associated with individual perturbation in the gut microbiome, and the microbial dynamics between SS and non-SS samples were different during the voyage. Moreover, the microbial signature for SS was identified using the variation of 19 bacterial species and 26 gene families. Furthermore, using a Random Forest model, SS was predicted with high accuracy (84.4%, area under the concentration-time curve = 0.91) based on 28 biomarkers from pre-voyage samples, and the prediction model was further validated by another 30-day voyage cohort (accuracy = 83.3%). The findings in this study provide insights to help us discover potential predictors or even therapeutic targets for dysbiosis-related diseases. IMPORTANCE Systemic and chronic diseases are important health problems today and have been proven to be strongly associated with dysbiotic gut microbiome. Studying the association between the gut microbiome and sub-optimal health status of humans in extreme environments (such as ocean voyages) will give us a better understanding of the interactions between observable health signs and a stable versus dysbiotic gut microbiome states. In this paper, we illustrated that ocean voyages could trigger different symptoms for different crew member cohorts due to individual differences; however, the co-occurrence of high prevalence symptoms indicated widespread perturbation of the gut microbiome. By investigating the microbial signature and gut microbiome dynamics, we demonstrated that such sub-optimal health status can be predicted even before the voyage. We termed this phenomenon as "seafaring syndrome." This study not only provides the potential strategy for health management in extreme environments but also can assist the prediction of other dysbiosis-related diseases.

The endophytome (plant-associated microbiome): methodological approaches, biological aspects, and biotech applications

Similar to other organisms, plants establish interactions with a variety of microorganisms in their natural environment. The plant microbiome occupies the host plant's tissues, either internally or on its surfaces, showing interactions that can assist in its growth, development, and adaptation to face environmental stresses. The advance of metagenomics and metatranscriptomics approaches has strongly driven the study and recognition of plant microbiome impacts. Research in this regard provides comprehensive information about the taxonomic and functional aspects of microbial plant communities, contributing to a better understanding of their dynamics. Evidence of the plant microbiome's functional potential has boosted its exploitation to develop more ecological and sustainable agricultural practices that impact human health. Although microbial inoculants' development and use are promising to revolutionize crop production, interdisciplinary studies are needed to identify new candidates and promote effective practical applications. On the other hand, there are challenges in understanding and analyzing complex data generated within a plant microbiome project's scope. This review presents aspects about the complex structuring and assembly of the microbiome in the host plant's tissues, metagenomics, and metatranscriptomics approaches for its understanding, covering descriptions of recent studies concerning metagenomics to characterize the microbiome of non-model plants under different aspects. Studies involving bio-inoculants, isolated from plant microbial communities, capable of assisting in crops' productivity, are also reviewed.

Microbial ecology of sulfur cycling near the sulfate-methane transition of deep-sea cold seep sediments

Microbial sulfate reduction is largely associated with anaerobic methane oxidation and alkane degradation in sulfate-methane transition zone (SMTZ) of deep-sea cold seeps. How the sulfur cycling is mediated by microbes near SMTZ has not been fully understood. In this study, we detected a shallow SMTZ in three of eight sediment cores sampled from two cold seep areas in the South China Sea. One hundred ten genomes representing sulfur-oxidizing bacteria (SOB) and sulfur-reducing bacteria (SRB) strains were identified from three SMTZ-bearing cores. In the layers above SMTZ, SOB were mostly constituted by Campylobacterota, Gammaproteobacteria and Alphaproteobacteria that probably depended on nitrogen oxides and/or oxygen for oxidation of sulfide and thiosulfate in near-surface sediment layers. In the layers below the SMTZ, the deltaproteobacterial SRB genomes and metatranscriptomes revealed CO₂ fixation by Wood-Ljungdahl pathway, sulfate reduction and nitrogen fixation for syntrophic or fermentative lifestyle. A total of 68% of the metagenome assembled genomes were not adjacent to known species in a phylogenomic tree, indicating a high diversity of bacteria involved in sulfur cycling. With the large number of genomes for SOB and SRB, our study uncovers the microbial populations that potentially mediate sulfur metabolism and associated carbon and nitrogen cycles, which sheds light on complex biogeochemical processes in deep-sea environments.

A Scale-Free, Fully Connected Global Transition Network Underlies Known Microbiome Diversity

Microbiomes are inherently linked by their structural similarity, yet the global features of such similarity are not clear. Here, we propose as a solution a search-based microbiome transition network. By traversing a composition-similarity-based network of 177,022 microbiomes, we show that although the compositions are distinct by habitat, each microbiome is on-average only seven neighbors from any other microbiome on Earth, indicating the inherent homology of microbiomes at the global scale. This network is scale-free, suggesting a high degree of stability and robustness in microbiome transition. By tracking the minimum spanning tree in this network, a global roadmap of microbiome dispersal was derived that tracks the potential paths of formulating and propagating microbiome diversity. Such search-based global microbiome networks, reconstructed within hours on just one computing node, provide a readily expanded reference for tracing the origin and evolution of existing or new microbiomes. IMPORTANCE It remains unclear whether and how compositional changes at the "community to community" level among microbiomes are linked to the origin and evolution of global microbiome diversity. Here we propose a microbiome transition model and a network-based analysis framework to describe and simulate the variation and dispersal of the global microbial beta-diversity across multiple habitats. The traversal of a transition network with 177,022 samples shows the inherent homology of microbiome at the global scale. Then a global roadmap of microbiome dispersal derived from the network tracks the potential paths of formulating and propagating microbiome diversity. Such search-based microbiome network provides a readily expanded reference for tracing the origin and evolution of existing or new microbiomes at the global scale.

Active microbial ecosystem in glacier basal ice fuelled by iron and silicate comminution-derived hydrogen

The basal zone of glaciers is characterized by physicochemical properties that are distinct from firnified ice due to strong interactions with underlying substrate and bedrock. Basal ice (BI) ecology and the roles that the microbiota play in biogeochemical cycling, weathering, and proglacial soil formation remain poorly described. We report on basal ice geochemistry, bacterial diversity (16S rRNA gene phylogeny), and inferred ecological roles at three temperate Icelandic glaciers. We sampled three physically distinct basal ice facies (stratified, dispersed, and debris bands) and found facies dependent on biological similarities and differences; basal ice character is therefore an important sampling consideration in future studies. Based on a high abundance of silicates and Fe-containing minerals and, compared to earlier BI literature, total C was detected that could sustain the basal ice ecosystem. It was hypothesized that C-fixing chemolithotrophic bacteria, especially Fe-oxidisers and hydrogenotrophs, mutualistically support associated heterotrophic communities. Basal ice-derived rRNA gene sequences corresponding to genera known to harbor hydrogenotrophic methanogens suggest that silicate comminution-derived hydrogen can also be utilized for methanogenesis. PICRUSt-predicted metabolism suggests that methane metabolism and C-fixation pathways could be highly relevant in BI, indicating the importance of these metabolic routes. The nutrients and microbial communities release from melting basal ice may play an important role in promoting pioneering communities establishment and soil development in deglaciating forelands.

Gut Microbiota and Urine Metabonomics Alterations in Constitution after Chinese Medicine and Lifestyle Intervention

Traditional Chinese Medicine Constitution (TCMC) divides human beings into balanced (ping-he) constitution (PH) and unbalanced constitution. Yang-deficiency (yang-xu) constitution (YAX) is one of the most common unbalanced constitutions in Chinese general population, and it causes susceptibility to particular diseases. However, unbalanced constitutions can be regulated by Chinese medicine and lifestyle intervention in clinical practice. Gui-fu-di-huang-wan (GFDHW) is a well-known Chinese medicine with yang-invigorating activity and is regarded as improving YAX. In this study, 60 healthy YAX students selected from a prospective population of 5185 were enrolled in a randomized clinical trial and completed the study. We compared the gut microbiota and urinary metabolome between individuals with PH and those with YAX before and after one-month-intervention. Compared with the control group, the health status of the intervention group improved significantly, the YAX symptom score was reduced, and the efficacy remained high at the one-year follow-up. The gut microbiota of the healthy PH exhibited greater diversity, and significantly higher species were identified. Compared to PH group, YAX individuals showed increased abundance of Bacteroidetes and Bacteroides, also had higher levels of gut microbial-derived urinary metabolites. After one-month-intervention, both GFDHW treatment and lifestyle intervention enriched the diversity and modulated the structure in YAX. The intervention group also partially restored the microbiome and metabolome to healthy PH-like levels. Further, a microbiota co-occurrence network analysis showed that the metabolites enriched in YAX were correlated with microbial community structure. Taken together, our results suggest that Chinese medicine combined with lifestyle intervention benefits YAX individuals. Gut microbiota/metabolite crosstalk might be involved in the Chinese medicine-mediated effects.

The predictive power of saliva electrolytes exceeds that of saliva microbiomes in diagnosing early childhood caries

Early childhood caries (ECC) is one of the most prevalent chronic diseases affecting children worldwide, and thus its etiology, diagnosis, and prognosis are of particular clinical significance. This study aims to test the ability of salivary microbiome and electrolytes in diagnosing ECC, and their interplays within the same population. We here simultaneously profiled salivary microbiome and biochemical components of 331 children (166 caries-free (H group) and 165 caries-active children (C group)) aged 4-6 years. We identified both salivary microbial and biochemical dysbiosis associated with ECC. Remarkably, K⁺, Cl^-, NH₄⁺, Na⁺, SO₄^2-, Ca²⁺, Mg²⁺, and Br^- were enriched while pH and NO₃^- were depleted in ECC. Moreover, the dmft index (ECC severity) positively correlated with Cl^-, NH₄⁺, Ca²⁺, Mg²⁺, Br^-, while negatively with pH and NO₃^-. Furthermore, machine-learning classification models were constructed based on these biomarkers from saliva microbiota, or electrolytes (and pH). Unexpectedly, the electrolyte-based classifier (AUROC = 0.94) outperformed microbiome-based (AUROC = 0.70) one and the composite-based one (with both microbial and biochemical data; AUC = 0.89) in predicting ECC. Collectively, these findings indicate ECC-associated alterations and interplays in the oral microbiota, electrolytes and pH, underscoring the necessity of developing diagnostic models with predictors from salivary electrolytes.

Standardization of microbiome studies for urolithiasis: an international consensus agreement

Numerous metagenome-wide association studies (MWAS) for urolithiasis have been published, leading to the discovery of potential interactions between the microbiome and urolithiasis. However, questions remain about the reproducibility, applicability and physiological relevance of these data owing to discrepancies in experimental technique and a lack of standardization in the field. One barrier to interpreting MWAS is that experimental biases can be introduced at every step of the experimental pipeline, including sample collection, preservation, storage, processing, sequencing, data analysis and validation. Thus, the introduction of standardized protocols that maintain the flexibility to achieve study-specific objectives is urgently required. To address this need, the first international consortium for microbiome in urinary stone disease - MICROCOSM - was created and consensus panel members were asked to participate in a consensus meeting to develop standardized protocols for microbiome studies if they had published an MWAS on urolithiasis. Study-specific protocols were revised until a consensus was reached. This consensus group generated standardized protocols, which are publicly available via a secure online server, for each step in the typical clinical microbiome-urolithiasis study pipeline. This standardization creates the benchmark for future studies to facilitate consistent interpretation of results and, collectively, to lead to effective interventions to prevent the onset of urolithiasis, and will also be useful for investigators interested in microbiome research in other urological diseases.

Towards multi-label classification: Next step of machine learning for microbiome research

Machine learning (ML) has been widely used in microbiome research for biomarker selection and disease prediction. By training microbial profiles of samples from patients and healthy controls, ML classifiers constructs data models by community features that highly correlated with the target diseases, so as to determine the status of new samples. To clearly understand the host-microbe interaction of specific diseases, previous studies always focused on well-designed cohorts, in which each sample was exactly labeled by a single status type. However, in fact an individual may be associated with multiple diseases simultaneously, which introduce additional variations on microbial patterns that interferes the status detection. More importantly, comorbidities or complications can be missed by regular ML models, limiting the practical application of microbiome techniques. In this review, we summarize the typical ML approaches of single-label classification for microbiome research, and demonstrate their limitations in multi-label disease detection using a real dataset. Then we prospect a further step of ML towards multi-label classification that potentially solves the aforementioned problem, including a series of promising strategies and key technical issues for applying multi-label classification in microbiome-based studies.

Characterization of bacterial communities associated with blood-fed and starved tropical bed bugs, Cimex hemipterus (F.) (Hemiptera): a high throughput metabarcoding analysis

With the development of new metagenomic techniques, the microbial community structure of common bed bugs, Cimex lectularius, is well-studied, while information regarding the constituents of the bacterial communities associated with tropical bed bugs, Cimex hemipterus, is lacking. In this study, the bacteria communities in the blood-fed and starved tropical bed bugs were analysed and characterized by amplifying the v3-v4 hypervariable region of the 16S rRNA gene region, followed by MiSeq Illumina sequencing. Across all samples, Proteobacteria made up more than 99% of the microbial community. An alpha-proteobacterium Wolbachia and gamma-proteobacterium, including Dickeya chrysanthemi and Pseudomonas, were the dominant OTUs at the genus level. Although the dominant OTUs of bacterial communities of blood-fed and starved bed bugs were the same, bacterial genera present in lower numbers were varied. The bacteria load in starved bed bugs was also higher than blood-fed bed bugs.

Longitudinal Multi-omics and Microbiome Meta-analysis Identify an Asymptomatic Gingival State That Links Gingivitis, Periodontitis, and Aging

A significant portion of world population still fails to brush teeth daily. As a result, the majority of the global adult population is afflicted with chronic gingivitis, and if it is left untreated, some of them will eventually suffer from periodontitis.

Most adults experience episodes of gingivitis, which can progress to the irreversible, chronic state of periodontitis, yet roles of plaque in gingivitis onset and progression to periodontitis remain elusive. Here, we longitudinally profiled the plaque metagenome, the plaque metabolome, and salivary cytokines in 40 adults who transited from naturally occurring gingivitis (NG) to healthy gingivae (baseline) and then to experimental gingivitis (EG). During EG, rapid and consistent alterations in plaque microbiota, metabolites, and salivary cytokines emerged as early as 24 to 72 h after oral-hygiene pause, defining an asymptomatic suboptimal health (SoH) stage of the gingivae. SoH features a swift, full activation of 11 salivary cytokines but a steep synergetic decrease of plaque-derived betaine and Rothia spp., suggesting an anti-gum inflammation mechanism by health-promoting symbionts. Global, cross-cohort meta-analysis revealed, at SoH, a greatly elevated microbiome-based periodontitis index driven by its convergence of both taxonomical and functional profiles toward the periodontitis microbiome. Finally, post-SoH gingivitis development accelerates oral microbiota aging by over 1 year within 28 days, with Rothia spp. depletion and Porphyromonas gingivalis elevation as hallmarks. Thus, the microbiome-defined, transient gum SoH stage is a crucial link among gingivitis, periodontitis, and aging.

Starvation Alters Gut Microbiome in Black Soldier Fly (Diptera: Stratiomyidae) Larvae

Unlike for vertebrates, the impact of starvation on the gut microbiome of invertebrates is poorly studied. Deciphering shifts in metabolically active associated bacterial communities in vertebrates has led to determining the role of the associated microbiome in the sensation of hunger and discoveries of associated regulatory mechanisms. From an invertebrate perspective, such as the black soldier fly, such information could lead to enhanced processes for optimized biomass production and waste conversion. Bacteria associated with food substrates of black soldier fly are known to impact corresponding larval life-history traits (e.g., larval development); however, whether black soldier fly larval host state (i.e., starved) impacts the gut microbiome is not known. In this study, we measured microbial community structural and functional shifts due to black soldier fly larvae starvation. Data generated demonstrate such a physiological state (i.e., starvation) does in fact impact both aspects of the microbiome. At the phylum level, community diversity decreased significantly during black soldier fly larval starvation (p = 0.0025). Genus level DESeq2 analysis identified five genera with significantly different relative abundance (q < 0.05) across the 24 and 48 H post initiation of starvation: Actinomyces, Microbacterium, Enterococcus, Sphingobacterium, and Leucobacter. Finally, we inferred potential gene function and significantly predicted functional KEGG Orthology (KO) abundance. We demonstrated the metabolically active microbial community structure and function could be influenced by host-feeding status. Such perturbations, even when short in duration (e.g., 24 H) could stunt larval growth and waste conversion due to lacking a full complement of bacteria and associated functions.

Metagenomic insights into the effect of sulfate on enhanced biological phosphorus removal

Excess phosphorus in water supplies causes eutrophication, which degrades water quality. Hence, the efficient removal of phosphorus from wastewater represents a highly desirable process. Here, we evaluated the effect of sulfate concentration on enhanced biological phosphorus removal (EBPR), in which phosphorus is typically removed under anaerobic-oxic cycles, with sulfate reduction the predominant process in the anaerobic phase. Two sequencing batch EBPR reactors operated under high- (SBR-H) vs. low-sulfate (SBR-L) concentrations for 189 days and under three periods, i.e., start-up, sufficient acetate, and limited acetate. Under acetate-rich conditions, phosphorus removal efficiency was > 90% for both reactors; however, under acetate-limited conditions, only 34% and 91.3% of the phosphorus were removed for the SBR-L and the SBR-H, respectively. Metagenomic sequencing of the reactors showed that the relative abundance of the polyphosphate-accumulating and sulfur-reducing bacteria (SRB) was higher in the SBR-H, consistent with its higher phosphorus removal activity. Ten high-quality metagenome-assembled genomes, including one closely related to the genus Thiothrix disciformis (99.81% average amino acid identity), were recovered and predicted to simultaneously metabolize phosphorus and sulfur by the presence of phosphorus (ppk, ppx, pst, and pit) and sulfur (sul, sox, dsr, sqr, apr, cys, and sat) metabolism marker genes. The omics-based analysis provided a holistic view of the microbial ecosystem in the EBPR process and revealed that SRB and Thiothrix play key roles in the presence of high sulfate.Key points• We observed high phosphorus-removal efficiency in high-sulfate EBPR.• Metagenome-based analysis revealed sulfate-related metabolic mechanisms in EBPR.• SRB and PAOs showed interrelationships in the EBPR-sulfur systems.

Association between indoor microbiome exposure and sick building syndrome (SBS) in junior high schools of Johor Bahru, Malaysia

Sick building syndrome (SBS) is a collection of nonspecific syndromes linked with the built environment. The occurrence of SBS is associated with humidity, ventilation, moulds and microbial compounds exposure. However, no study has reported the association between indoor microbiome and SBS. In this study, 308 students were surveyed for SBS symptoms from 21 classrooms of 7 junior high schools from Johor Bahru, Malaysia, and vacuum dust from floor, desks and chairs was collected. High throughput amplicon sequencing (16S rRNA gene and ITS region) and quantitative PCR were conducted to characterize the absolute concentration of bacteria and fungi taxa. In total, 326 bacterial and 255 fungal genera were detected in dust with large compositional variation among classrooms. Also, half of these samples showed low compositional similarity to microbiome data deposited in the public database. The number of observed OTUs in Gammaproteobacteria was positively associated with SBS (p = 0.004). Eight microbial genera were associated with SBS (p < 0.01). Bacterial genera, Rhodomicrobium, Scytonema and Microcoleus, were protectively (negatively) associated with ocular and throat symptoms and tiredness, and Izhakiella and an unclassified genus from Euzebyaceae were positively associated with the throat and ocular symptoms. Three fungal genera, Polychaeton, Gympopus and an unclassified genus from Microbotryaceae, were mainly positively associated with tiredness. The associations differed with our previous study in microbial compounds (endotoxin and ergosterol) and SBS in the same population, in which nasal and dermal symptoms were affected. A higher indoor relative humidity and visible dampness or mould in classrooms were associated with a higher concentration of potential risk bacteria and a lower concentration of potential protective bacteria (p < 0.01). This is the first study to characterize the SBS-associated microorganisms in the indoor environment, revealing complex interactions between microbiome, SBS symptoms and environmental characteristics.

Microbiome Search Engine 2: a Platform for Taxonomic and Functional Search of Global Microbiomes on the Whole-Microbiome Level

A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird’s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile.

Metagenomic data sets from diverse environments have been growing rapidly. To ensure accessibility and reusability, tools that quickly and informatively correlate new microbiomes with existing ones are in demand. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes in the global metagenome data space based on the taxonomic or functional similarity of a whole microbiome to those in the database. MSE 2 consists of (i) a well-organized and regularly updated microbiome database that currently contains over 250,000 metagenomic shotgun and 16S rRNA gene amplicon samples associated with unified metadata collected from 798 studies, (ii) an enhanced search engine that enables real-time and fast (<0.5 s per query) searches against the entire database for best-matched microbiomes using overall taxonomic or functional profiles, and (iii) a Web-based graphical user interface for user-friendly searching, data browsing, and tutoring. MSE 2 is freely accessible via http://mse.ac.cn. For standalone searches of customized microbiome databases, the kernel of the MSE 2 search engine is provided at GitHub (https://github.com/qibebt-bioinfo/meta-storms).

IMPORTANCE A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird’s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile. Key improvements include database extension, data compatibility, a search engine kernel, and a user interface. The new ability to search the microbiome space via functional similarity greatly expands the scope of search-based mining of the microbiome big data.

Meta-Apo improves accuracy of 16S-amplicon-based prediction of microbiome function

BACKGROUND

Due to their much lower costs in experiment and computation than metagenomic whole-genome sequencing (WGS), 16S rRNA gene amplicons have been widely used for predicting the functional profiles of microbiome, via software tools such as PICRUSt 2. However, due to the potential PCR bias and gene profile variation among phylogenetically related genomes, functional profiles predicted from 16S amplicons may deviate from WGS-derived ones, resulting in misleading results.

RESULTS

Here we present Meta-Apo, which greatly reduces or even eliminates such deviation, thus deduces much more consistent diversity patterns between the two approaches. Tests of Meta-Apo on > 5000 16S-rRNA amplicon human microbiome samples from 4 body sites showed the deviation between the two strategies is significantly reduced by using only 15 WGS-amplicon training sample pairs. Moreover, Meta-Apo enables cross-platform functional comparison between WGS and amplicon samples, thus greatly improve 16S-based microbiome diagnosis, e.g. accuracy of gingivitis diagnosis via 16S-derived functional profiles was elevated from 65 to 95% by WGS-based classification. Therefore, with the low cost of 16S-amplicon sequencing, Meta-Apo can produce a reliable, high-resolution view of microbiome function equivalent to that offered by shotgun WGS.

CONCLUSIONS

This suggests that large-scale, function-oriented microbiome sequencing projects can probably benefit from the lower cost of 16S-amplicon strategy, without sacrificing the precision in functional reconstruction that otherwise requires WGS. An optimized C++ implementation of Meta-Apo is available on GitHub ( https://github.com/qibebt-bioinfo/meta-apo ) under a GNU GPL license. It takes the functional profiles of a few paired WGS:16S-amplicon samples as training, and outputs the calibrated functional profiles for the much larger number of 16S-amplicon samples.

The Role of the Gut Microbiome in Resisting Norovirus Infection as Revealed by a Human Challenge Study

Norovirus infections take a heavy toll on worldwide public health. While progress has been made toward understanding host responses to infection, the role of the gut microbiome in determining infection outcome is unknown. Moreover, data are lacking on the nature and duration of the microbiome response to norovirus infection, which has important implications for diagnostics and host recovery. Here, we characterized the gut microbiomes of subjects enrolled in a norovirus challenge study. We analyzed microbiome features of asymptomatic and symptomatic individuals at the genome (population) and gene levels and assessed their response over time in symptomatic individuals. We show that the preinfection microbiomes of subjects with asymptomatic infections were enriched in Bacteroidetes and depleted in Clostridia relative to the microbiomes of symptomatic subjects. These compositional differences were accompanied by differences in genes involved in the metabolism of glycans and sphingolipids that may aid in host resilience to infection. We further show that microbiomes shifted in composition following infection and that recovery times were variable among human hosts. In particular, Firmicutes increased immediately following the challenge, while Bacteroidetes and Proteobacteria decreased over the same time. Genes enriched in the microbiomes of symptomatic subjects, including the adenylyltransferase glgC, were linked to glycan metabolism and cell-cell signaling, suggesting as-yet unknown roles for these processes in determining infection outcome. These results provide important context for understanding the gut microbiome role in host susceptibility to symptomatic norovirus infection and long-term health outcomes.IMPORTANCE The role of the human gut microbiome in determining whether an individual infected with norovirus will be symptomatic is poorly understood. This study provides important data on microbes that distinguish asymptomatic from symptomatic microbiomes and links these features to infection responses in a human challenge study. The results have implications for understanding resistance to and treatment of norovirus infections.

Exploring the Influence of Signal Molecules on Marine Biofilms Development

Microbes respond to environmental stimuli through complicated signal transduction systems. In microbial biofilms, because of complex multiple species interactions, signals transduction systems are of an even higher complexity. Here, we performed a signal-molecule-treatment experiment to study the role of different signal molecules, including N-hexanoyl-L-homoserine lactone (C6-HSL), N-dodecanoyl-L-homoserine lactone (C12-HSL), Pseudomonas quinolone signal (PQS), and cyclic di-GMP (c-di-GMP), in the development of marine biofilms. Comparative metagenomics suggested a distinctive influence of these molecules on the microbial structure and function of multi-species biofilm communities in its developing stage. The PQS-treated biofilms shared the least similarity with the control and initial biofilms. The role of PQS in biofilm development was further explored experimentally with the strain Erythrobacter sp. HKB8 isolated from marine biofilms. Comparative transcriptomic analysis showed that 314 genes, such as those related to signal transduction and biofilm formation, were differentially expressed in the untreated and PQS-treated Erythrobacter sp. HKB8 biofilms. Our study demonstrated the different roles of signal molecules in marine biofilm development. In particular, the PQS-based signal transduction system, which is frequently detected in marine biofilms, may play an important role in regulating microbe-microbe interactions and the assemblage of biofilm communities.

Comparison of Bacterial Microbiota in Raw Mare's Milk and Koumiss Using PacBio Single Molecule Real-Time Sequencing Technology

Koumiss is a traditional fermented raw mare’s milk product. It contains high nutritional value and is well-known for its health-promoting effect as an alimentary supplement. This study aimed to investigate the bacterial diversity, especially lactic acid bacteria (LAB), in koumiss and raw mare’s milk. Forty-two samples, including koumiss and raw mare’s milk, were collected from the pastoral area in Yili, Kazakh Autonomous Prefecture, Xinjiang Uygur Autonomous Region in China. This work applied PacBio single-molecule real-time (SMRT) sequencing to profile full-length 16S rRNA genes, which was a powerful technology enabling bacterial taxonomic assignment to the species precision. The SMRT sequencing identified 12 phyla, 124 genera, and 227 species across 29 koumiss samples. Eighteen phyla, 286 genera, and 491 species were found across 13 raw mare’s milk samples. The bacterial microbiota diversity of the raw mare’s milk was more complex and diverse than the koumiss. Raw mare’s milk was rich in LAB, such as Lactobacillus (L.) helveticus, L. plantarum, Lactococcus (Lc.) lactis, and L. kefiranofaciens. In addition, raw mare’s milk also contained sequences representing pathogenic bacteria, such as Staphylococcus succinus, Acinetobacter lwoffii, Klebsiella (K.) oxytoca, and K. pneumoniae. The koumiss microbiota mainly comprised LAB, and sequences representing pathogenic bacteria were not detected. Meanwhile, the koumiss was enriched with secondary metabolic pathways that were potentially beneficial for health. Using a Random Forest model, the two kinds of samples could be distinguished with a high accuracy 95.2% [area under the curve (AUC) = 0.98] based on 42 species and functions. Comprehensive depiction of the microbiota in raw mare’s milk and koumiss might help elucidate evolutionary and functional relationships among the bacterial communities in these dairy products. The current work suffered from the limitation of a low sample size, so further work would be required to verify our findings.

The Enhanced Pharmacological Effects of Modified Traditional Chinese Medicine in Attenuation of Atherosclerosis Is Driven by Modulation of Gut Microbiota

Accumulating evidence indicated that gut microbiota-targeted therapy is a promising strategy to treat Cardiovascular Disease (CVD). Traditional Chinese Medicine (TCM) has been used in CVD treatments for over 2,000 years which is believed to result from the modulation of gut microbiota, yet the underlying mechanism remains elusive. According to the theoretical system of TCM, we developed an innovative formula of TCM named "TongMai ZhuYu (TMZY)" on top of one classic Chinese herbal formula ["XueFu ZhuYu (XFZY)"], which can more effectively alleviate CVD in the clinical practice. Here, we first systematically assessed the pharmacological effects of TMZY, XFZY, and atorvastatin on atherosclerosis (AS) induced by high-fat diet (HFD) in rats. TMZY typically outperformed others in alleviating AS rats by characterization of pathological morphology, immunohistochemistry, inflammatory cytokines. Remarkably, combining this modified TCM formula (TMZY) with atorvastatin can further help the alleviation of AS in rats by suppressing immune and inflammatory responses. Furthermore, to test whether TMZY alleviated AS symptoms by altering gut microbial compositions (dysbiosis), we employed 16S amplicon sequencing to investigate gut microbiota changes in the AS mice induced by high choline diet (HCD) using both TMZY and XFZY under antibiotic-treated and untreated conditions. TCM formulas induced consistent and remarkable changes in the phenotypes and microbiota in the HCD mice. TMZY modulated more changes in the gut microbiota to improve diseased phenotypes than XFZY. Notably, the TMZY-intervention effect on CVD in mice attenuated after the suppression of gut microbial activity by antibiotics. Collectively, we demonstrated that TCM herbals could effectively modulate the gut microbiota as a mechanism for altering the pathogenesis of cardiovascular disorders in mice/rats.

Comparative gut microbiome analysis of the Prakriti and Sasang systems reveals functional level similarities in constitutionally similar classes

The traditional medicinal systems (TMS) of India (Prakriti) and Korea (Sasang) classify human individuals based on their constitution determined by the physiological and psychological traits of individuals. Similarities in the constitutions are already found between the classes of Prakriti (Vata, Pitta, and Kapha) and Sasang (TE: Taeeumin, SE: Soeumin, and SY: Soyangin) systems. Gut health is an important aspect of this constitution based classification in TMS. To determine the role of gut microbes in such classifications, we have analyzed the gut microbiome (taxa and imputed functions) in the constitutionally similar Prakriti and Sasang classes. An enrichment of Bacteroides and Prevotella enterotypes is observed in the Sasang and Prakriti samples, respectively. The impact of the constitution is found to be more prominent with respect to the taxa and predicted-functions within the Prakriti classes. Gut microbiome functional-level similarities are found to correlate well with the host phenotypes of the constitutionally similar Prakriti and Sasang classes. An enrichment of carbohydrate and amino-acid metabolism is observed in the Vata and SE classes which may be responsible for meeting with their high energy demands and lean phenotype. The Pitta and SY classes exhibit the high capacity to metabolize toxins. An enrichment of functions responsible for predisposition to obesity and high drug metabolism is observed in the Kapha and TE classes. The contribution of gut adaptive functions is found to correlate with the constitution-based classification in both Prakriti and Sasang systems. The TE class harboured the highest number of biofilm-forming and stress-tolerant microbes thus exhibiting the maximum tolerance of environmental stress. Similarities in the gut microbiota and the resulting disease predisposition patterns are found to exist between the constitutionally matching Prakriti and Sasang classes.

Method development for cross-study microbiome data mining: Challenges and opportunities

During the past decade, tremendous amount of microbiome sequencing data has been generated to study on the dynamic associations between microbial profiles and environments. How to precisely and efficiently decipher large-scale of microbiome data and furtherly take advantages from it has become one of the most essential bottlenecks for microbiome research at present. In this mini-review, we focus on the three key steps of analyzing cross-study microbiome datasets, including microbiome profiling, data integrating and data mining. By introducing the current bioinformatics approaches and discussing their limitations, we prospect the opportunities in development of computational methods for the three steps, and propose the promising solutions to multi-omics data analysis for comprehensive understanding and rapid investigation of microbiome from different angles, which could potentially promote the data-driven research by providing a broader view of the "microbiome data space".

Correlation-Centric Network (CCN) representation for microbial co-occurrence patterns: new insights for microbial ecology

Mainstream studies of microbial community focused on critical organisms and their physiology. Recent advances in large-scale metagenome analysis projects initiated new researches in the complex correlations between large microbial communities. Specifically, previous studies focused on the nodes (i.e. species) of the Species-Centric Networks (SCNs). However, little was understood about the change of correlation between network members (i.e. edges of the SCNs) when the network was disturbed. Here, we introduced a Correlation-Centric Network (CCN) to the microbial research based on the concept of edge networks. In CCN, each node represented a species-species correlation, and edge represented the species shared by two correlations. In this research, we investigated the CCNs and their corresponding SCNs on two large cohorts of microbiome. The results showed that CCNs not only retained the characteristics of SCNs, but also contained information that cannot be detected by SCNs. In addition, when the members of microbial communities were decreased (i.e. environmental disturbance), the CCNs fluctuated within a small range in terms of network connectivity. Therefore, by highlighting the important species correlations, CCNs could unveil new insights when studying not only the functions of target species, but also the stabilities of their residing microbial communities.

Impact of short-term overfeeding of saturated or unsaturated fat or sugars on the gut microbiota in relation to liver fat in obese and overweight adults

BACKGROUNDS & AIMS

Intestinal microbiota may be causally involved in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). We aimed to study the effect of short-term overfeeding on human gut microbiota in relation to baseline and overfeeding-induced liver steatosis. We also asked whether the baseline microbiota composition is associated to the overfeeding-induced increase in liver fat.

METHODS

In a randomized trial, 38 overweight and obese subjects were assigned to consume an excess of 1000 kcal/day of diets rich in either saturated fat, unsaturated fat, or simple sugars for 3 weeks. Fasting blood samples and ¹H-MR spectroscopy were used for extensive clinical phenotyping as previously reported (PMID: 29844096). Fecal samples were collected for the analysis of the gut microbiota using 16S rRNA amplicon sequencing, imputed metagenomics and qPCR. Microbiota results were correlated with dietary intakes and clinical measurements before and during overfeeding.

RESULTS

The overall community structure of the microbiota remained highly stable and personalized during overfeeding based on between-sample Bray-Curtis dissimilarity, but the relative abundances of individual taxa were altered in a diet-specific manner: overfeeding saturated fat increased Proteobacteria, while unsaturated fat increased butyrate producers. Sugar overfeeding increased Lactococcus and Escherichia coli. Imputed functions of the gut microbiota were not affected by overfeeding. Several taxa affected by overfeeding significantly correlated with the changes in host metabolic markers. The baseline levels of proteobacterial family Desulfovibrionaceae, and especially genus Bilophila, were significantly associated to overfeeding-induced liver fat increase independently of the diet arm. In general, limited overlap was observed between the overfeeding-induced microbiota changes and the liver fat-associated microbiota features at baseline.

CONCLUSIONS

Our work indicates that the human gut microbiota is resilient to short-term overfeeding on community level, but specific taxa are altered on diet composition-dependent manner. Generalizable microbiota signatures directly associated with liver steatosis could not be identified. Instead, the carriage of Bilophila was identified as a potential novel risk factor for diet-induced liver steatosis in humans. Clinical trial registry number: NCT02133144 listed on NIH website: ClinicalTrials.gov.

Metagenomic 16S rDNA amplicon data on bacterial diversity profiling and its predicted metabolic functions of varillales in Allpahuayo-Mishana National Reserve

The white-sands forests or varillales of the Peruvian Amazon are characterized by their distinct physical characteristics, patchy distribution, and endemism [1, 2]. Much research has been conducted on the specialized plant and animal communities that inhabit these ecosystems, yet their soil microbiomes have yet to be studied. Here we provide metagenomic 16S rDNA amplicon data of soil microbiomes from three types of varillales in Allpahuayo-Mishana National Reserve near Iquitos, Peru. Composite soil samples were collected from very low varillal, high-dry varillal, and high-wet varillal. Purified metagenomic DNA was used to prepare and sequence 16S rDNA metagenomic libraries on the Illumina MiqSeq platform. Raw paired-endsequences were analyzed using the Metagenomics RAST server (MG-RAST) and Parallel-Meta3 software and revealed the existence of a high percentage of undiscovered sequences, potentially indicating specialized bacterial communities in these forests. Also, were predicted several metabolic functions in this dataset. The raw sequence data in fastq format is available in the public repository Discover Mendeley Data (https://data.mendeley.com/datasets/syktzxcnp6/2). Also, is available at NCBI's Sequence Read Archive (SRA) with accession numbers SRX7891206 (very low varillal), SRX7891207 (high-dry varillal), and SRX7891208 (high-wet varillal).

Computational profiling of the gut-brain axis: microflora dysbiosis insights to neurological disorders

Almost 2500 years after Hippocrates' observations on health and its direct association to the gastrointestinal tract, a paradigm shift has recently occurred, making the gut and its symbionts (bacteria, fungi, archaea and viruses) a point of convergence for studies. It is nowadays well established that the gut microflora's compositional diversity regulates via its genes (the microbiome) the host's health and provides preliminary insights into disease progression and regulation. The microbiome's involvement is evident in immunological and physiological studies that link changes in its biodiversity to its contributions to the host's phenotype but also in neurological investigations, substantiating the aptly named gut-brain axis. The definitive mechanisms of this last bidirectional interaction will be our main focus because it presents researchers with a new conundrum. In this review, we prospect current literature for computational analysis methodologies that accommodate the need for better understanding of the microbiome-gut-brain interactions and neurological disorder onset and progression, through cross-disciplinary systems biology applications. We will present bioinformatics tools used in exploring these synergies that help build and interpret microbial 16S ribosomal RNA data sets, produced by shotgun and high-throughput sequencing of healthy and neurological disorder samples stored in biological databases. These approaches provide alternative means for researchers to form hypotheses to their inquests faster, cheaper and swith precision. The goal of these studies relies on the integration of combined metagenomics and metabolomics assessments. An accurate characterization of the microbiome and its functionality can support new diagnostic, prognostic and therapeutic strategies for neurological disorders, customized for each individual host.

Structure and function of the Arctic and Antarctic marine microbiota as revealed by metagenomics

BACKGROUND

The Arctic and Antarctic are the two most geographically distant bioregions on earth. Recent sampling efforts and following metagenomics have shed light on the global ocean microbial diversity and function, yet the microbiota of polar regions has not been included in such global analyses.

RESULTS

Here a metagenomic study of seawater samples (n = 60) collected from different depths at 28 locations in the Arctic and Antarctic zones was performed, together with metagenomes from the Tara Oceans. More than 7500 (19%) polar seawater-derived operational taxonomic units could not be identified in the Tara Oceans datasets, and more than 3,900,000 protein-coding gene orthologs had no hits in the Ocean Microbial Reference Gene Catalog. Analysis of 214 metagenome assembled genomes (MAGs) recovered from the polar seawater microbiomes, revealed strains that are prevalent in the polar regions while nearly undetectable in temperate seawater. Metabolic pathway reconstruction for these microbes suggested versatility for saccharide and lipids biosynthesis, nitrate and sulfate reduction, and CO₂ fixation. Comparison between the Arctic and Antarctic microbiomes revealed that antibiotic resistance genes were enriched in the Arctic while functions like DNA recombination were enriched in the Antarctic.

CONCLUSIONS

Our data highlight the occurrence of dominant and locally enriched microbes in the Arctic and Antarctic seawater with unique functional traits for environmental adaption, and provide a foundation for analyzing the global ocean microbiome in a more complete perspective. Video abstract.

Multiple-Disease Detection and Classification across Cohorts via Microbiome Search

Here, we present a search-based strategy for disease detection and classification, which detects diseased samples via their outlier novelty versus a database of samples from healthy subjects and then compares them to databases of samples from patients. This approach enables the identification of microbiome states associated with disease even in the presence of different cohorts, multiple sequencing platforms, or significant contamination.

Microbiome-based disease classification depends on well-validated disease-specific models or a priori organismal markers. These are lacking for many diseases. Here, we present an alternative, search-based strategy for disease detection and classification, which detects diseased samples via their outlier novelty versus a database of samples from healthy subjects and then compares these to databases of samples from patients. Our strategy’s precision, sensitivity, and speed outperform model-based approaches. In addition, it is more robust to platform heterogeneity and to contamination in 16S rRNA gene amplicon data sets. This search-based strategy shows promise as an important first step in microbiome big-data-based diagnosis.

IMPORTANCE Here, we present a search-based strategy for disease detection and classification, which detects diseased samples via their outlier novelty versus a database of samples from healthy subjects and then compares them to databases of samples from patients. This approach enables the identification of microbiome states associated with disease even in the presence of different cohorts, multiple sequencing platforms, or significant contamination.

Meta-analysis Reveals Potential Influence of Oxidative Stress on the Airway Microbiomes of Cystic Fibrosis Patients

The lethal chronic airway infection of the cystic fibrosis (CF) patients is predisposed by colonization of specific CF-philic pathogens or the CF microbiomes, but key processes and reasons of the microbiome settlement in the patients are yet to be fully understood, especially their survival and metabolic dynamics from normal to diseased status under treatment. Here, we report our meta-analysis results on CF airway microbiomes based on metabolic networks reconstructed from genome information at species level. The microbiomes of CF patients appear to engage much more redox-related activities than those of controls, and by constructing a large dataset of anti-oxidative stress (anti-OS) genes, our quantitative evaluation of the anti-OS capacity of each bacterial species in the CF microbiomes confirms strong conservation of the anti-OS responses within genera and also shows that the CF pathogens have significantly higher anti-OS capacity than commensals and other typical respiratory pathogens. In addition, the anti-OS capacity of a relevant species correlates with its relative fitness for the airways of CF patients over that for the airways of controls. Moreover, the total anti-OS capacity of the respiratory microbiome of CF patients is collectively higher than that of controls, which increases with disease progression, especially after episodes of acute exacerbation and antibiotic treatment. According to these results, we propose that the increased OS in the airways of CF patients may play an important role in reshaping airway microbiomes to a more resistant status that favors the pre-infection colonization of the CF pathogens for a higher anti-OS capacity.