SILVA, RDP, Greengenes, NCBI and OTT - how do these taxonomies compare?

Comparative analysis of bacterial community structure and physicochemical quality in high-temperature Daqu of different colors in Qingzhou production area

To compare the effects of differences in Daqu making technology and production regions on the bacterial composition and physicochemical properties of high-temperature Daqu (HTD), this study analyzed the bacterial community structure of three colors of HTD in the Qingzhou production area and measured their physicochemical quality. At the same time, a comparative analysis was conducted on the bacterial composition of Qingzhou and Xiangyang regions. The results revealed that the HTD in the Qingzhou area exhibited a diverse bacterial community dominated by Lentibacillus, Scopulibacillus, and Staphylococcus. The black HTD displayed the lowest bacterial richness (P < 0.05) and a relatively unique microbial structure. Significant variations were observed in the physicochemical qualities of the three colors of HTD. Notably, white HTD demonstrated higher moisture and ash content, saccharification and liquor-producing power. Yellow HTD exhibited higher amino nitrogen and protein content, and black HTD displayed higher water activity, acidity, and starch content. The variation in Bacillus, Limosilactobacillus, and Weissella distributions across different colors of HTD primarily contributed to these findings. From the HTD samples in the Qingzhou area, Bacillus (61.90 %) and lactic acid bacteria (17.46 %) being the predominant cultivable communities. Cluster analysis identified significant differences in bacterial communities among HTD samples from various production areas. It can enhance the understanding of HTD quality in the Qingzhou area and offer insights for optimizing HTD and Maotai-flavor Baijiu quality.

Effects of Eimeria acervulina infection on the luminal and mucosal microbiota of the cecum and ileum in broiler chickens

Coccidiosis, an intestinal disease caused by Eimeria parasites, is responsible for major losses in the poultry industry by impacting chicken health. The gut microbiota is associated with health factors, such as nutrient exchange and immune system modulation, requiring understanding on the effects of Eimeria infection on the gut microbiota. This study aimed to determine the effects of Eimeria acervulina infection on the luminal and mucosal microbiota of the cecum (CeL and CeM) and ileum (IlL and IlM) at multiple time points (days 3, 5, 7, 10, and 14) post-infection. E. acervulina infection decreased evenness in CeL microbiota at day 10, increased richness in CeM microbiota at day 3 before decreasing richness at day 14, and decreased richness in IlL microbiota from day 3 to 10. CeL, CeM, and IlL microbiota differed between infected and control birds based on beta diversity at varying time points. Infection reduced relative abundance of bacterial taxa and some predicted metabolic pathways known for short-chain fatty acid production in CeL, CeM, and IlL microbiota, but further understanding of metabolic function is required. Despite E. acervulina primarily targeting the duodenum, our findings demonstrate the infection can impact bacterial diversity and abundance in the cecal and ileal microbiota.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Analysis of fungal diversity in the gut feces of wild takin (Budorcas taxicolor)

Introduction

The composition of the intestinal microbiome correlates significantly with an animal's health status. Hence, this indicator is highly important and sensitive for protecting endangered animals. However, data regarding the fungal diversity of the wild Budorcas taxicolor (takin) gut remain scarce. Therefore, this study analyzes the fungal diversity, community structure, and pathogen composition in the feces of wild B. taxicolor.

Methods

To ensure comprehensive data analyses, we collected 82 fecal samples from five geographical sites. Amplicon sequencing of the internal transcribed spacer (ITS) rRNA was used to assess fecal core microbiota and potential pathogens to determine whether the microflora composition is related to geographical location or diet. We further validated the ITS rRNA sequencing results via amplicon metagenomic sequencing and culturing of fecal fungi.

Results and discussion

The fungal diversity in the feces of wild Budorcas taxicolor primarily comprised three phyla (99.69%): Ascomycota (82.19%), Fungi_unclassified (10.37%), and Basidiomycota (7.13%). At the genus level, the predominant fungi included Thelebolus (30.93%), Functional_unclassified (15.35%), and Ascomycota_unclassified (10.37%). Within these genera, certain strains exhibit pathogenic properties, such as Thelebolus, Cryptococcus, Trichosporon, Candida, Zopfiella, and Podospora. Collectively, this study offers valuable information for evaluating the health status of B. taxicolor and formulating protective strategies.

Effect of wheat crops on the persistence and attenuation of antibiotic resistance genes in soil after swine wastewater application

Swine wastewater (SW) application introduces antibiotic resistance genes (ARGs) into farmland soils. However, ARG attenuation in SW-fertigated soils, especially those influenced by staple crops and soil type, remains unclear. This study investigated twelve soil ARGs and one mobile genetic element (MGE) in sandy loam, loam, and silt loam soils before and after SW application in wheat-planted and unplanted soils. The results revealed an immediate increase in the abundance of ARGs in soil by two orders of magnitude above background levels following SW application. After SW application, the soil total ARG abundance was attenuated, reaching background levels at 54 days; However, more individual ARGs were detected above the detection limit than pre-application. Among the 13 genes, acc(6')-lb, tetM, and tetO tended to persist in the soil during wheat harvest. ARG half-lives were up to four times longer in wheat-planted soils than in bare soils. Wheat planting decreased the persistence of acc(6')-lb, ermB, ermF, and intI2 but increased the persistence of others such as sul1 and sul2. Soil type had no significant impact on ARG and MGE fates. Our findings emphasize the need for strategic SW application and the consideration of crop cultivation effects to mitigate ARG accumulation in farmland soils.

Microbiologic surveys for Baijiu fermentation are affected by experimental design

The traditional Chinese alcoholic beverage Baijiu is produced by spontaneous fermentation of grains under anaerobic conditions. While numerous studies have used metagenomic technology to investigate the microbiome of Baijiu brewing, the microbial succession mechanism of Baijiu brewing has not been fully clarified, and metagenomic strategies for microecology surveys have not been comprehensively evaluated. Using the fermentation process of strong-flavor Baijiu as a model, we compared the data for bacterial communities based on short read 16S rRNA variable regions, V3-V4, and full-length 16S regions, V1-V9, to whole metagenomic shotgun sequencing (WMS) to measure the effect of technology selection on phylogenetic and functional profiles. The results showed differences in bacterial compositions and their relation to volatiles and physicochemical variables between sequencing methods. Furthermore, the percentage of V3-V4 sequences assigned to species level was higher than the percentage of V1-V9 sequences according to SILVA taxonomy, but lower according to NCBI taxonomy (P < 0.05). In both SILVA and NCBI taxonomies, the relative abundances of bacterial communities at both the genus and family levels were more positively correlated with WMS data in the V3-V4 dataset than in the V1-V9 dataset. The WMS identified changes in abundances of multiple metabolic pathways during fermentation (P < 0.05), including "starch and sucrose metabolism," "galactose metabolism," and "fatty acid biosynthesis." Although functional predictions derived from 16S data show similar patterns to WMS, most metabolic pathway changes are uncorrelated (P > 0.05). This study provided new technical and biological insights into Baijiu production that may assist in selection of methodologies for studies of fermentation systems.

Comparison of MALDI-TOF mass spectrometry and 16S rDNA sequencing for identification of environmental bacteria: a case study of cave mussel-associated culturable microorganisms

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is routinely used as a rapid and cost-effective method for pathogen identification in clinical settings. In comparison, its performance in other microbiological fields, such as environmental microbiology, is still being tested, although isolates of environmental microbes are essential for in-depth in vivo studies of their biology, including biotechnological applications. We investigated the applicability of MALDI-TOF MS for the identification of bacterial isolates from a highly oligotrophic environment - Dinaric Karst caves, which likely harbor specific microorganisms. We cultured bacteria from the shell surface of the endemic mussel Congeria jalzici, one of the three known cave mussels in the world that lives in the Dinaric karst underground. The bacterial isolates were obtained by swabbing the shell surface of mussels living in microhabitats with different amounts of water: 10 air-exposed mussels, 10 submerged mussels, and 10 mussels in the hygropetric zone. A collection of 87 pure culture isolates was obtained, mostly belonging to the phylum Bacillota (72%), followed by Pseudomonadota (16%), Actinomycetota (11%), and Bacteroidota (1%). We compared the results of MALDI-TOF MS identification (Bruker databases DB-5989 and version 11, v11) with the results of 16S rDNA-based phylogenetic analysis, a standard procedure for bacterial identification. Identification to the genus level based on 16S rDNA was possible for all isolates and clearly outperformed the results from MALDI-TOF MS, although the updated MALDI-TOF MS database v11 gave better results than the DB-5989 version (85% versus 62%). However, identification to the species-level by 16S rDNA sequencing was achieved for only 17% of isolates, compared with 14% and 40% for the MALDI-TOF MS databases DB-5989 and v11 database, respectively. In conclusion, our results suggest that continued enrichment of MALDI-TOF MS libraries will result with this method soon becoming a rapid, accurate, and efficient tool for assessing the diversity of culturable bacteria from different environmental niches.

Dynamics of soil biota and nutrients at varied depths in a Tamarix ramosissima-dominated natural desert ecosystem: Implications for nutrient cycling and desertification management

The underground community of soil organisms, known as soil biota, plays a critical role in terrestrial ecosystems. Different ecosystems exhibit varied responses of soil organisms to soil physical and chemical properties (SPCPs). However, our understanding of how soil biota react to different soil depths in naturally established population of salinity tolerant Tamarix ramosissima in desert ecosystems, remains limited. To address this, we employed High-Throughput Illumina HiSeq Sequencing to examine the population dynamics of soil bacteria, fungi, archaea, protists, and metazoa at six different soil depths (0-100 cm) in the naturally occurring T. ramosissima dominant zone within the Taklimakan desert of China. Our observations reveal that the alpha diversity of bacteria, fungi, metazoa, and protists displayed a linear decrease with the increase of soil depth, whereas archaea exhibited an inverse pattern. The beta diversity of soil biota, particularly metazoa, bacteria, and protists, demonstrated noteworthy associations with soil depths through Non-Metric Dimensional Scaling analysis. Among the most abundant classes of soil organisms, we observed Actinobacteria, Sordariomycetes, Halobacteria, Spirotrichea, and Nematoda for bacteria, fungi, archaea, protists, and metazoa, respectively. Additionally, we identified associations between the vertical distribution of dominant biotic communities and SPCPs. Bacterial changes were mainly influenced by total potassium, available phosphorus (AP), and soil water content (SWC), while fungi were impacted by nitrate (NO3-) and available potassium (AK). Archaea showed correlations with total carbon (TC) and AK thus suggesting their role in methanogenesis and methane oxidation, protists with AP and SWC, and metazoa with AP and pH. These correlations underscore potential connections to nutrient cycling and the production and consumption of greenhouse gases (GhGs). This insight establishes a solid foundation for devising strategies to mitigate nutrient cycling and GHG emissions in desert soils, thereby playing a pivotal role in the advancement of comprehensive approaches to sustainable desert ecosystem management.

Considerations for the inclusion of metabarcoding data in the plant protection product risk assessment of the soil microbiome

There is increasing interest in further developing the plant protection product (PPP) environmental risk assessment, particularly within the European Union, to include the assessment of soil microbial community composition, as measured by metabarcoding approaches. However, to date, there has been little discussion as to how this could be implemented in a standardized, reliable, and robust manner suitable for regulatory decision-making. Introduction of metabarcoding-based assessments of the soil microbiome into the PPP risk assessment would represent a significant increase in the degree of complexity of the data that needs to be processed and analyzed in comparison to the existing risk assessment on in-soil organisms. The bioinformatics procedures to process DNA sequences into community compositional data sets currently lack standardization, while little information exists on how these data should be used to generate regulatory endpoints and the ways in which these endpoints should be interpreted. Through a thorough and critical review, we explore these challenges. We conclude that currently, we do not have a sufficient degree of standardization or understanding of the required bioinformatics and data analysis procedures to consider their use in an environmental risk assessment context. However, we highlight critical knowledge gaps and the further research required to understand whether metabarcoding-based assessments of the soil microbiome can be utilized in a statistically and ecologically relevant manner within a PPP risk assessment. Only once these challenges are addressed can we consider if and how we should use metabarcoding as a tool for regulatory decision-making to assess and monitor ecotoxicological effects on soil microorganisms within an environmental risk assessment of PPPs. Integr Environ Assess Manag 2024;20:337-358. © 2023 SETAC.

Species-level resolution for the vaginal microbiota with short amplicons

Specific bacterial species have been found to play important roles in human vagina. Achieving high species-level resolution is vital for analyzing vaginal microbiota data. However, contradictory conclusions were yielded from different methodological studies. More comprehensive evaluation is needed for determining an optimal pipeline for vaginal microbiota. Based on the sequences of vaginal bacterial species downloaded from NCBI, we conducted simulated amplification with various primer sets targeting different 16S regions as well as taxonomic classification on the amplicons applying different combinations of algorithms (BLAST+, VSEARCH, and Sklearn) and reference databases (Greengenes2, SILVA, and RDP). Vaginal swabs were collected from participants with different vaginal microecology to construct 16S full-length sequenced mock communities. Both computational and experimental amplifications were performed on the mock samples. Classification accuracy of each pipeline was determined. Microbial profiles were compared between the full-length and partial 16S sequencing samples. The optimal pipeline was further validated in a multicenter cohort against the PCR results of common STI pathogens. Pipeline V1-V3_Sklearn_Combined had the highest accuracy for classifying the amplicons generated from both the NCBI downloaded data (84.20% ± 2.39%) and the full-length sequencing data (95.65% ± 3.04%). Vaginal samples amplified and sequenced targeting the V1-V3 region but merely employing the forward reads (223 bp) and classified using the optimal pipeline, resembled the mock communities the most. The pipeline demonstrated high F1-scores for detecting STI pathogens within the validation cohort. We have determined an optimal pipeline to achieve high species-level resolution for vaginal microbiota with short amplicons, which will facilitate future studies.IMPORTANCEFor vaginal microbiota studies, diverse 16S rRNA gene regions were applied for amplification and sequencing, which affect the comparability between different studies as well as the species-level resolution of taxonomic classification. We conducted comprehensive evaluation on the methods which influence the accuracy for the taxonomic classification and established an optimal pipeline to achieve high species-level resolution for vaginal microbiota with short amplicons, which will facilitate future studies.

Time-Course Responses of Apple Leaf Endophytes to the Infection of Gymnosporangium yamadae

Apple rust, caused by Gymnosporangium yamadae, poses a significant challenge to apple production. Prior studies have underscored the pivotal role played by endophytic microbial communities, intimately linked with the host, in influencing plant diseases and their pathogenic outcomes. The objective of this study is to scrutinize alternations in endophytic microbial communities within apple leaves at different stages of apple rust using high-throughput sequencing technology. The findings revealed a discernible pattern characterized by an initial increase and subsequent decrease in the alpha diversity of microbial communities in diseased leaves. A microbial co-occurrence network analysis revealed that the complexity of the bacterial community in diseased leaves diminished initially and then rebounded during the progression of the disease. Additionally, employing the PICRUSt2 platform, this study provided preliminary insights into the functions of microbial communities at specific disease timepoints. During the spermogonial stage, endophytic bacteria particularly exhibited heightened activity in genetic information processing, metabolism, and environmental information processing pathways. Endophytic fungi also significantly enriched a large number of metabolic pathways during the spermogonial stage and aecial stage, exhibiting abnormally active life activities. These findings establish a foundation for comprehending the role of host endophytes in the interaction between pathogens and hosts. Furthermore, they offer valuable insights for the development and exploitation of plant endophytic resources, thereby contributing to enhanced strategies for managing apple rust.

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.

The impact of gut microbiome enterotypes on ulcerative colitis: identifying key bacterial species and revealing species co-occurrence networks using machine learning

Ulcerative colitis (UC) is a chronic inflammatory intestinal disease affecting the colon and rectum, with its pathogenesis attributed to genetic background, environmental factors, and gut microbes. This study aimed to investigate the role of enterotypes in UC by conducting a hierarchical analysis, determining differential bacteria using machine learning, and performing Species Co-occurrence Network (SCN) analysis. Fecal bacterial data were collected from UC patients, and a 16S rRNA metagenomic analysis was performed using the QIIME2 bioinformatics pipeline. Enterotype clustering was conducted at the family level, and deep neural network (DNN) classification models were trained for UC and healthy controls (HC) in each enterotype. Results from eleven 16S rRNA gut microbiome datasets revealed three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Clostridiaceae (ET-C). Ruminococcus (R. gnavus) abundance was significantly higher in UC subjects with ET-B and ET-C than in those with ET-L. R. gnavus also showed a positive correlation with Clostridia in UC SCN for ET-B and ET-C subjects, with a higher correlation in ET-C subjects. Conversely, Odoribacter (O.) splanchnicus and Bacteroides (B.) uniformis exhibited a positive correlation with tryptophan metabolism and AMP-activated protein kinase (AMPK) signaling pathways, while R. gnavus showed a negative correlation. In vitro co-culture experiments with Clostridium (C.) difficile demonstrated that fecal microbiota from ET-B subjects had a higher abundance of C. difficile than ET-L subjects. In conclusion, the ET-B enterotype predisposes individuals to UC, with R. gnavus as a potential risk factor and O. splanchnicus and B. uniformis as protective bacteria, and those with UC may have ultimately become ET-C.

Streptomyces Diversity Maps Reveal Distinct High-Specificity Biogeographical and Environmental Patterns Compared to the Overall Bacterial Diversity

Despite their enormous impact on the environment and humans, the distribution and variety of the biggest natural secondary metabolite producers, the genus Streptomyces, have not been adequately investigated. We developed representative maps from public EMP 16S rRNA amplicon sequences microbiomics data. Streptomyces ASVs were extracted from the EMP overall bacterial community, demonstrating Streptomyces diversity and identifying crucial diversity patterns. Our findings revealed that while the EMP primarily distinguished bacterial communities as host-associated or free-living (EMPO level 1), the Streptomyces community showed no significant difference but exhibited distinctions between categories in EMPO level 2 (animal, plant, non-saline, and saline). Multiple linear regression analysis demonstrated that pH, temperature, and salinity significantly predicted Streptomyces richness, with richness decreasing as these factors increased. However, latitude and longitude do not predict Streptomyces richness. Our Streptomyces maps revealed that additional samplings in Africa and Southeast Asia are needed. Additionally, our findings indicated that a greater number of samples did not always result in greater Streptomyces richness; future surveys may not necessitate extensive sampling from a single location. Broader sampling, rather than local/regional sampling, may be more critical in answering microbial biogeograph questions. Lastly, using 16S rRNA gene sequencing data has some limitations, which should be interpreted cautiously.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

Microbial metabolites regulate social novelty via CaMKII neurons in the BNST

Social novelty is a cognitive process that is essential for animals to interact strategically with conspecifics based on their prior experiences. The commensal microbiome in the gut modulates social behavior through various routes, including microbe-derived metabolite signaling. Short-chain fatty acids (SCFAs), metabolites derived from bacterial fermentation in the gastrointestinal tract, have been previously shown to impact host behavior. Herein, we demonstrate that the delivery of SCFAs directly into the brain disrupts social novelty through distinct neuronal populations. We are the first to observe that infusion of SCFAs into the lateral ventricle disrupted social novelty in microbiome-depleted mice without affecting brain inflammatory responses. The deficit in social novelty can be recapitulated by activating calcium/calmodulin-dependent protein kinase II (CaMKII)-labeled neurons in the bed nucleus of the stria terminalis (BNST). Conversely, chemogenetic silencing of the CaMKII-labeled neurons and pharmacological inhibition of fatty acid oxidation in the BNST reversed the SCFAs-induced deficit in social novelty. Our findings suggest that microbial metabolites impact social novelty through a distinct neuron population in the BNST.

Social and psychological adversity are associated with distinct mother and infant gut microbiome variations

Health disparities are driven by underlying social disadvantage and psychosocial stressors. However, how social disadvantage and psychosocial stressors lead to adverse health outcomes is unclear, particularly when exposure begins prenatally. Variations in the gut microbiome and circulating proinflammatory cytokines offer potential mechanistic pathways. Here, we interrogate the gut microbiome of mother-child dyads to compare high-versus-low prenatal social disadvantage, psychosocial stressors and maternal circulating cytokine cohorts (prospective case-control study design using gut microbiomes from 121 dyads profiled with 16 S rRNA sequencing and 89 dyads with shotgun metagenomic sequencing). Gut microbiome characteristics significantly predictive of social disadvantage and psychosocial stressors in the mothers and children indicate that different discriminatory taxa and related pathways are involved, including many species of Bifidobacterium and related pathways across several comparisons. The lowest inter-individual gut microbiome similarity was observed among high-social disadvantage/high-psychosocial stressors mothers, suggesting distinct environmental exposures driving a diverging gut microbiome assembly compared to low-social disadvantage/low-psychosocial stressors controls (P = 3.5 × 10-5 for social disadvantage, P = 2.7 × 10-15 for psychosocial stressors). Children's gut metagenome profiles at 4 months also significantly predicted high/low maternal prenatal IL-6 (P = 0.029), with many bacterial species overlapping those identified by social disadvantage and psychosocial stressors. These differences, based on maternal social and psychological status during a critical developmental window early in life, offer potentially modifiable targets to mitigate health inequities.

Comparisons of the Oral Microbiota from Seven Species of Wild Venomous Snakes in Taiwan Using the High-Throughput Amplicon Sequencing of the Full-Length 16S rRNA Gene

A venomous snake's oral cavity may harbor pathogenic microorganisms that cause secondary infection at the wound site after being bitten. We collected oral samples from 37 individuals belonging to seven species of wild venomous snakes in Taiwan, including Naja atra (Na), Bungarus multicinctus (Bm), Protobothrops mucrosquamatus (Pm), Trimeresurus stejnegeri (Ts), Daboia siamensis (Ds), Deinagkistrodon acutus (Da), and alpine Trimeresurus gracilis (Tg). Bacterial species were identified using full-length 16S rRNA amplicon sequencing analysis, and this is the first study using this technique to investigate the oral microbiota of multiple Taiwanese snake species. Up to 1064 bacterial species were identified from the snake's oral cavities, with 24 pathogenic and 24 non-pathogenic species among the most abundant ones. The most abundant oral bacterial species detected in our study were different from those found in previous studies, which varied by snake species, collection sites, sampling tissues, culture dependence, and analysis methods. Multivariate analysis revealed that the oral bacterial species compositions in Na, Bm, and Pm each were significantly different from the other species, whereas those among Ts, Ds, Da, and Tg showed fewer differences. Herein, we reveal the microbial diversity in multiple species of wild snakes and provide potential therapeutic implications regarding empiric antibiotic selection for wildlife medicine and snakebite management.

The respiratory microbiota and its impact on health and disease in dogs and cats: A One Health perspective

Healthy lungs were long thought of as sterile, with presence of bacteria identified by culture representing contamination. Recent advances in metagenomics have refuted this belief by detecting rich, diverse, and complex microbial communities in the healthy lower airways of many species, albeit at low concentrations. Although research has only begun to investigate causality and potential mechanisms, alterations in these microbial communities (known as dysbiosis) have been described in association with inflammatory, infectious, and neoplastic respiratory diseases in humans. Similar studies in dogs and cats are scarce. The microbial communities in the respiratory tract are linked to distant microbial communities such as in the gut (ie, the gut-lung axis), allowing interplay of microbes and microbial products in health and disease. This review summarizes considerations for studying local microbial communities, key features of the respiratory microbiota and its role in the gut-lung axis, current understanding of the healthy respiratory microbiota, and examples of dysbiosis in selected respiratory diseases of dogs and cats.

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes. IMPORTANCE Mapping the interrelationships between different species in a microbial community is important for understanding and controlling their structure and function. The surge in the high-throughput sequencing of microbial communities has led to the creation of thousands of data sets containing information about microbial abundances. These abundances can be transformed into co-occurrence networks, providing a glimpse into the associations within microbiomes. However, processing these data sets to obtain co-occurrence information relies on several complex steps, each of which involves numerous choices of tools and corresponding parameters. These multiple options pose questions about the robustness and uniqueness of the inferred networks. In this study, we address this workflow and provide a systematic analysis of how these choices of tools affect the final network and guidelines on appropriate tool selection for a particular data set. We also develop a consensus network algorithm that helps generate more robust co-occurrence networks based on benchmark synthetic data sets.

Biofilm colonization of stone materials from an Australian outdoor sculpture: Importance of geometry and exposure

The safeguarding of Australian outdoor stone heritage is currently limited by a lack of information concerning mechanisms responsible for the degradation of the built heritage. In this study, the bacterial community colonizing the stone surface of an outdoor sculpture located at the Church of St. John the Evangelist in Melbourne was analysed, providing an overview of the patterns of microbial composition associated with stone in an anthropogenic context. Illumina MiSeq 16S rRNA gene sequencing together with confocal laser microscope investigations highlighted the bacterial community was composed of both phototrophic and chemotrophic microorganisms characteristic of stone and soil, and typical of arid, salty and urban environments. Cardinal exposure, position and surface geometry were the most important factors in determining the structure of the microbial community. The North-West exposed areas on the top of the sculpture with high light exposure gave back the highest number of sequences and were dominated by Cyanobacteria. The South and West facing in middle and lower parts of the sculpture received significantly lower levels of radiation and were dominated by Actinobacteria. Proteobacteria were observed as widespread on the sculpture. This pioneer research provided an in-depth investigation of the microbial community structure on a deteriorated artistic stone in the Australian continent and provides information for the identification of deterioration-associated microorganisms and/or bacteria beneficial for stone preservation.

Gut dysbiosis in Thai intrahepatic cholangiocarcinoma and hepatocellular carcinoma

Primary liver cancer (PLC), which includes intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC), has the highest incidence of all cancer types in Thailand. Known etiological factors, such as viral hepatitis and chronic liver disease do not fully account for the country's unusually high incidence. However, the gut-liver axis, which contributes to carcinogenesis and disease progression, is influenced by the gut microbiome. To investigate this relationship, fecal matter from 44 Thai PLC patients and 76 healthy controls were subjected to whole-genome metagenomic shotgun sequencing and then analyzed by marker gene-based and assembly based methods. Results revealed greater gut microbiome heterogeneity in iCCA compared to HCC and healthy controls. Two Veillonella species were found to be more abundant in iCCA samples and could distinguish iCCA from HCC and healthy controls. Conversely, Ruminococcus gnavus was depleted in iCCA patients and could distinguish HCC from iCCA samples. High Veillonella genus counts in the iCCA group were associated with enriched amino acid biosynthesis and glycolysis pathways, while enriched phospholipid and thiamine metabolism pathways characterized the HCC group with high Blautia genus counts. These findings reveal distinct landscapes of gut dysbiosis among Thai iCCA and HCC patients and warrant further investigation as potential biomarkers.

Intelligent Biological Networks: Improving Anti-Microbial Resistance Resilience through Nutritional Interventions to Understand Protozoal Gut Infections

Enteric protozoan pathogenic infections significantly contribute to the global burden of gastrointestinal illnesses. Their occurrence is considerable within remote and indigenous communities and regions due to reduced access to clean water and adequate sanitation. The robustness of these pathogens leads to a requirement of harsh treatment methods, such as medicinal drugs or antibiotics. However, in addition to protozoal infection itself, these treatments impact the gut microbiome and create dysbiosis. This often leads to opportunistic pathogen invasion, anti-microbial resistance, or functional gastrointestinal disorders, such as irritable bowel syndrome. Moreover, these impacts do not remain confined to the gut and are reflected across the gut-brain, gut-liver, and gut-lung axes, among others. Therefore, apart from medicinal treatment, nutritional supplementation is also a key aspect of providing recovery from this dysbiosis. Future proteins, prebiotics, probiotics, synbiotics, and food formulations offer a good solution to remedy this dysbiosis. Furthermore, nutritional supplementation also helps to build resilience against opportunistic pathogens and potential future infections and disorders that may arise due to the dysbiosis. Systems biology techniques have shown to be highly effective tools to understand the biochemistry of these processes. Systems biology techniques characterize the fundamental host-pathogen interaction biochemical pathways at various infection and recovery stages. This same mechanism also allows the impact of the abovementioned treatment methods of gut microbiome remediation to be tracked. This manuscript discusses system biology approaches, analytical techniques, and interaction and association networks, to understand (1) infection mechanisms and current global status; (2) cross-organ impacts of dysbiosis, particularly within the gut-liver and gut-lung axes; and (3) nutritional interventions. This study highlights the impact of anti-microbial resistance and multi-drug resistance from the perspective of protozoal infections. It also highlights the role of nutritional interventions to add resilience against the chronic problems caused by these phenomena.

The effects of long-term hexabromocyclododecanes contamination on microbial communities in the microcosms

The adaptation of microbial community to the long-term contamination of hexabromocyclododecanes (HBCDs) has not been well studied. Our previous study found that the HBCDs contamination in the microcosms constructed of sediments from two different mangrove forests in 8 months resulted in serious acidification (pH2-3). This study reanalyzed previous sequencing data and compared them with data after 20 months to investigate the adaptive properties of microbial communities in the stress of HBCDs and acidification. It hypothesized that the reassembly was based on the fitness of taxa. The results indicated that eukaryotes and fungi might have better adaptive capacity to these deteriorated habitats. Eukaryotic taxa Eufallia and Syncystis, and fungal taxa Wickerhamomyces were only detected after 20 months of contamination. Moreover, eukaryotic taxa Caloneis and Nitzschia, and fungal taxa Talaromyces were dominant in most of microbial communities (14.467-95.941%). The functional compositions were sediment-dependent and more divergent than community reassemblies. Network and co-occurrence analysis suggested that acidophiles such as Acidisoma and Acidiphilium were gaining more positive relations in the long-term stress. The acidophilic taxa and genes involved in resistance to the acidification and toxicity of HBCDs were enriched, for example, bacteria Acidisoma and Acidiphilium, archaea Thermogymnomonas, and eukaryotes Nitzschia, and genes kdpC, odc1, polA, gst, and sod-2. These genes involved in oxidative stress response, energy metabolism, DNA damage repair, potassium transportation, and decarboxylation. It suggested that the microbial communities might cope with the stress from HBCDs and acidification via multiple pathways. The present research shed light on the evolution of microbial communities under the long-term stress of HBCDs contamination and acidification.

Significant Broad-Spectrum Antiviral Activity of Bi121 against Different Variants of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has so far infected 762 million people with over 6.9 million deaths worldwide. Broad-spectrum viral inhibitors that block the initial stages of infection by reducing virus binding and proliferation, thereby reducing disease severities, are still an unmet global medical need. We studied Bi121, which is a standardized polyphenolic-rich compound isolated from Pelargonium sidoides, against recombinant vesicular stomatitis virus (rVSV)-pseudotyped SARS-CoV-2S (mutations in the spike protein) of six different variants of SARS-CoV-2. Bi121 was effective at neutralizing all six rVSV-ΔG-SARS-CoV-2S variants. The antiviral activity of Bi121 was also assessed against SARS-CoV-2 variants (USA WA1/2020, Hongkong/VM20001061/2020, B.1.167.2 (Delta), and Omicron) in Vero cells and HEK-ACE2 cell lines using RT-qPCR and plaque assays. Bi121 showed significant antiviral activity against all the four SARS-CoV-2 variants tested, suggesting a broad-spectrum activity. Bi121 fractions generated using HPLC showed antiviral activity in three fractions out of eight against SARS-CoV-2. The dominant compound identified in all three fractions using LC/MS/MS analysis was Neoilludin B. In silico structural modeling studies with Neoilludin B showed that it has a novel RNA-intercalating activity toward RNA viruses. In silico findings and the antiviral activity of this compound against several SARS-CoV-2 variants support further evaluation as a potential treatment of COVID-19.

The Microbiome of Osteoarthritic Hip and Knee Joints: A Prospective Multicenter Investigation

BACKGROUND

Recent advances in high-throughput DNA sequencing technologies have made it possible to characterize the microbial profile in anatomical sites previously assumed to be sterile. We used this approach to explore the microbial composition within joints of osteoarthritic patients.

METHODS

This prospective multicenter study recruited 113 patients undergoing hip or knee arthroplasty between 2017 and 2019. Demographics and prior intra-articular injections were noted. Matched synovial fluid, tissue, and swab specimens were obtained and shipped to a centralized laboratory for testing. Following DNA extraction, microbial 16S-rRNA sequencing was performed.

RESULTS

Comparisons of paired specimens indicated that each was a comparable measure for microbiological sampling of the joint. Swab specimens were modestly different in bacterial composition from synovial fluid and tissue. The 5 most abundant genera were Escherichia, Cutibacterium, Staphylococcus, Acinetobacter, and Pseudomonas. Although sample size varied, the hospital of origin explained a significant portion (18.5%) of the variance in the microbial composition of the joint, and corticosteroid injection within 6 months before arthroplasty was associated with elevated abundance of several lineages.

CONCLUSIONS

The findings revealed that prior intra-articular injection and the operative hospital environment may influence the microbial composition of the joint. Furthermore, the most common species observed in this study were not among the most common in previous skin microbiome studies, suggesting that the microbial profiles detected are not likely explained solely by skin contamination. Further research is needed to determine the relationship between the hospital and a "closed" microbiome environment. These findings contribute to establishing the baseline microbial signal and identifying contributing variables in the osteoarthritic joint, which will be valuable as a comparator in the contexts of infection and long-term arthroplasty success.

LEVEL OF EVIDENCE

Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

An Environmental DNA Primer for Microbial and Restoration Ecology

Environmental DNA (eDNA) sequencing-DNA collected from the environment from living cells or shed DNA-was first developed for working with microbes and has greatly benefitted microbial ecologists for decades since. These tools have only become increasingly powerful with the advent of metabarcoding and metagenomics. Most new studies that examine diverse assemblages of bacteria, archaea, protists, fungi, and viruses lean heavily into eDNA using these newer technologies, as the necessary sequencing technology and bioinformatic tools have become increasingly affordable and user friendly. However, eDNA methods are rapidly evolving, and sometimes it can feel overwhelming to simply keep up with the basics. In this review, we provide a starting point for microbial ecologists who are new to DNA-based methods by detailing the eDNA methods that are most pertinent, including study design, sample collection and storage, selecting the right sequencing technology, lab protocols, equipment, and a few bioinformatic tools. Furthermore, we focus on how eDNA work can benefit restoration and what modifications are needed when working in this subfield.

The Nonbacterial Microbiome: Fungal and Viral Contributions to the Preterm Infant Gut in Health and Disease

The intestinal microbiome is frequently implicated in necrotizing enterocolitis (NEC) pathogenesis. While no particular organism has been associated with NEC development, a general reduction in bacterial diversity and increase in pathobiont abundance has been noted preceding disease onset. However, nearly all evaluations of the preterm infant microbiome focus exclusively on the bacterial constituents, completely ignoring any fungi, protozoa, archaea, and viruses present. The abundance, diversity, and function of these nonbacterial microbes within the preterm intestinal ecosystem are largely unknown. Here, we review findings on the role of fungi and viruses, including bacteriophages, in preterm intestinal development and neonatal intestinal inflammation, with potential roles in NEC pathogenesis yet to be determined. In addition, we highlight the importance of host and environmental influences, interkingdom interactions, and the role of human milk in shaping fungal and viral abundance, diversity, and function within the preterm intestinal ecosystem.

Comparing the differences of prokaryotic microbial community between pit walls and bottom from Chinese liquor revealed by 16S rRNA gene sequencing

This study aims to explore the prokaryotic microbial community structures and diversity in pit mud from different depths, and provide a theoretical basis for the liquor production and further study of pit mud. The fermented pit muds of strong-flavor liquor from Yun distillery were taken as samples. The high-throughput sequencing approach, followed by bioinformatics analyses, was used to compare the differences in the prokaryotic microbial community between pit walls and bottom represented by samples. A total of 31 bacteria phyla and 2 archaea phyla were detected. The dominant phyla in YJ-S, YJ-Z, and YJ-X (sample name) were Proteobacteria and Firmicutes, while the dominant genera in them were Acinetobacter, Aminobacterium, and Lactobacillus. YJ-Z and YJ-X were the closest in species diversity. In species richness analysis, YJ-X was the highest, followed by YJ-Z, and YJ-S was the lowest; in species uniformity analysis, YJ-S was the highest, followed by YJ-Z, and YJ-X was the lowest. The function predicted by 16S rRNA genome showed that prokaryotic microbial function in pit mud was mainly concentrated in "Carbohydrate transport and metabolism" and "Amino acid transport and metabolism." Significant differences in prokaryotic microbial community and gene function prediction between pit walls and bottom were found in YJ-S, YJ-Z, and YJ-X (p < 0.05).

Advanced approaches for the diagnosis and chemoprevention of canine vector-borne pathogens and parasites-Implications for the Asia-Pacific region and beyond

Vector-borne pathogens (VBPs) of canines are a diverse range of infectious agents, including viruses, bacteria, protozoa and multicellular parasites, that are pernicious and potentially lethal to their hosts. Dogs across the globe are afflicted by canine VBPs, but the range of different ectoparasites and the VBPs that they transmit predominate in tropical regions. Countries within the Asia-Pacific have had limited prior research dedicated to exploring the epidemiology of canine VBPs, whilst the few studies that have been conducted show VBP prevalence to be high, with significant impacts on dog health. Moreover, such impacts are not restricted to dogs, as some canine VBPs are zoonotic. We reviewed the status of canine VBPs in the Asia-Pacific, with particular focus on nations in the tropics, whilst also investigating the history of VBP diagnosis and examining recent progress in the field, including advanced molecular methods, such as next-generation sequencing (NGS). These tools are rapidly changing the way parasites are detected and discovered, demonstrating a sensitivity equal to, or exceeding that of, conventional molecular diagnostics. We also provide a background to the armoury of chemopreventive products available for protecting dogs from VBP. Here, field-based research within high VBP pressure environments has underscored the importance of ectoparasiticide mode of action on their overall efficacy. The future of canine VBP diagnosis and prevention at a global level is also explored, highlighting how evolving portable sequencing technologies may permit diagnosis at point-of-care, whilst further research into chemopreventives will be essential if VBP transmission is to be effectively controlled.

Omnicrobe, an open-access database of microbial habitats and phenotypes using a comprehensive text mining and data fusion approach

The dramatic increase in the number of microbe descriptions in databases, reports, and papers presents a two-fold challenge for accessing the information: integration of heterogeneous data in a standard ontology-based representation and normalization of the textual descriptions by semantic analysis. Recent text mining methods offer powerful ways to extract textual information and generate ontology-based representation. This paper describes the design of the Omnicrobe application that gathers comprehensive information on habitats, phenotypes, and usages of microbes from scientific sources of high interest to the microbiology community. The Omnicrobe database contains around 1 million descriptions of microbe properties. These descriptions are created by analyzing and combining six information sources of various kinds, i.e. biological resource catalogs, sequence databases and scientific literature. The microbe properties are indexed by the Ontobiotope ontology and their taxa are indexed by an extended version of the taxonomy maintained by the National Center for Biotechnology Information. The Omnicrobe application covers all domains of microbiology. With simple or rich ontology-based queries, it provides easy-to-use support in the resolution of scientific questions related to the habitats, phenotypes, and uses of microbes. We illustrate the potential of Omnicrobe with a use case from the food innovation domain.

Microbial-Based Products to Control Soil-Borne Pathogens: Methods to Improve Efficacy and to Assess Impacts on Microbiome

Microbial-based products (either as biopesticide or biofertilizers) have a long history of application, though their use is still limited, mainly due to a perceived low and inconsistent efficacy under field conditions. However, their efficacy has always been compared to chemical products, which have a completely different mechanism of action and production process, following the chemical paradigm of agricultural production. This paradigm has also been applied to regulatory processes, particularly for biopesticides, making the marketing of microbial-based formulations difficult. Increased knowledge about bioinocula behavior after application to the soil and their impact on soil microbiome should foster better exploitation of microbial-based products in a complex environment such as the soil. Moreover, the multifunctional capacity of microbial strains with regard to plant growth promotion and protection should also be considered in this respect. Therefore, the methods utilized for these studies are key to improving the knowledge and understanding of microbial-based product activity and improving their efficacy, which, from farmers' point of view, is the parameter to assess the usefulness of a treatment. In this review, we are thus addressing aspects related to the production and formulation process, highlighting the methods that can be used to evaluate the functioning and impact of microbial-based products on soil microbiome, as tools supporting their use and marketing.

Long-term taxonomic and functional stability of the gut microbiome from human fecal samples

Appropriate storage of fecal samples is a critical step for unbiased analysis in human microbiome studies. The purpose of this study was to evaluate the stability of the fecal microbial community for up to 18 months. Ten healthy volunteers provided fecal samples at the Jeonbuk National University Hospital. Stool samples were stored under the following six conditions: four different storage temperatures (- 70 °C, - 20 °C, 4 °C, and room temperature [20-25 °C]) and two different collection tubes (OMNIgene-Gut and DNA/RNA shield-fecal collection tubes). The gut microbiome was analyzed with 16S rRNA sequencing. We compared the taxonomic composition, alpha diversity, beta diversity and inferred pathway abundance between the baseline and 18 months after storage. Samples collected in the DNA/RNA Shield-fecal collection tubes showed the best performance in preservation of the taxonomic composition at 18 months. Pairwise differences in alpha diversity metrics showed the least deviation from zero. The PERMANOVA test showed non-significant change of beta diversity metrics (Unweighted Unifrac: q-value 0.268; Weighted Unifrac: q-value 0.848). The functional stability was significantly well preserved in the DNA/RNA Shield-fecal collection tubes (adjusted p value < 0.05). Our results demonstrate the use of the DNA/RNA Shield-fecal collection tube as an alternative storage method for fecal samples to preserve the taxonomic and functional stability of the microbiome over a long term.

Anthropogenic degradation alter surface soil biogeochemical pools and microbial communities in an Andean temperate forest

Soil microbial communities regulate a myriad of critical biogeochemical functions in forest ecosystems. Anthropogenic disturbances in natural forests could drive major shifts in plant and microbial communities resulting in substantial biogeochemical alterations. We evaluated the effect of anthropogenic disturbances in the soils of Andean temperate forests with different levels of degradation: i) mature forest (MF), ii) secondary forest (SF), iii) degraded forest (DF), and iv) deforested site converted into a prairie (DP). We quantified total soil carbon, nitrogen and phosphorous (TC, TN, and TP), and available nutrient stocks. The soil microbial community structure (i.e., composition, diversity, and abundance) was assessed under each condition from amplicon sequence variants (ASVs) obtained via NGS-Illumina sequencing and subsequent microbiome analysis. There were no significant differences in TC, TN, and TP across the forested states (MF, SF, DF). The deforested site condition presented significantly higher soil TC, TN, and TP and the lowest C:N, C:P, and N:P ratios. The DP soil microbiome was significantly more diverse in bacteria (D' = 0.47 ± 0.04); and fungi (H' = 5.11 ± 0.33). The bacterial microbiome was dominated by Proteobacteria (45.35 ± 0.89 %), Acidobacteria (20.73 ± 1.48 %), Actinobacteria (12.59 ± 0.34 %), and Bacteroidetes (7.32 ± 0.36 %) phyla in all sites. The soil fungal community was dominated by the phyla Ascomycota (42.11 ± 0.95 %), Mortierellomycota (28.74 ± 2.25 %), Basidiomycota (24.61 ± 0.52), and Mucoromycota (2.06 ± 0.43 %). Yet, there were significant differences at the genus level across conditions. Forest to prairie conversion facilitated the introduction of exotic bacterial and fungal taxa associated with agricultural activities and livestock grazing (∼50 % of DP core microbiome composed of unique ASVs). For example, the ammonia-oxidizing bacteria community emerged as a dominant group in the DP soils, along with a reduction in the ectomycorrhizal fungi community. The surface soil microbial community was surprisingly resistant to forest degradation and did not show a clear succession along the degradation gradient, but it was strongly altered after deforestation.

Effects of Eimeria acervulina infection on the luminal and mucosal microbiota of the duodenum and jejunum in broiler chickens

The intestinal disease coccidiosis, caused by Eimeria parasites, impacts nutrient absorption in broiler chickens, leading to weight gain depression and major losses in the poultry industry. To develop alternatives to antibiotics for treating infected chickens, the gut microbiota has been researched because of its association with health factors such as nutrient exchange, immune system modulation, digestive system physiology, and pathogen exclusion. The aim of this study was to determine the effect of Eimeria acervulina infection on the luminal and mucosal microbiota of both the duodenum (DuoL and DuoM) and jejunum (JejL and JejM) at multiple time points (days 3, 5, 7, 10, and 14) post-infection. 16S rRNA amplicon sequencing was utilized to characterize the microbiota and analyze differences in alpha and beta diversity between infected (IF) and control (C) birds at each time point. Alpha diversity differed between IF and C birds in DuoM and JejM microbiota. Combined with beta diversity results, DuoM microbiota appeared to be affected by infection in the longer-term, while JejM microbiota were affected in the shorter-term. Relative abundances of bacterial taxa known for short-chain fatty acid (SCFA) production, such as Lachnospiraceae, Subdoligranulum, and Peptostreptococcaceae, tended to be lower in IF birds for all four microbiota. Moreover, predicted functional abundances showed MetaCyc pathways related to SCFA production, especially butyrate, may be influenced by these differences in bacterial relative abundance. Our findings expand understanding of how Eimeria infection affects luminal and mucosal microbiota in the duodenum and jejunum, and further research on metagenomic function may provide insights on the degree of influence duodenal and jejunal bacteria have on chicken health.

Screening Salamanders for Symbionts

Microbial symbionts are broadly categorized by their impacts on host fitness: commensals, pathogens, and mutualists. However, recent investigations into the physiological basis of these impacts have revealed nuanced microbial influences on a wide range of host developmental, immunological, and physiological processes, including regeneration. Exploring these impacts begins with knowing which microbes are present. This methodological pipeline contains both targeted assays using PCR and culturing, as well as culture-independent approaches, to survey host salamander tissues for common and unknown microbial symbionts.

The gut microbiota and depressive symptoms across ethnic groups

The gut microbiome is thought to play a role in depressive disorders, which makes it an attractive target for interventions. Both the microbiome and depressive symptom levels vary substantially across ethnic groups. Thus, any intervention for depression targeting the microbiome requires understanding of microbiome-depression associations across ethnicities. Analysing data from the HELIUS cohort, we characterize the gut microbiota and its associations with depressive symptoms in 6 ethnic groups (Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish, Moroccan; N = 3211), living in the same urban area. Diversity of the gut microbiota, both within (α-diversity) and between individuals (β-diversity), predicts depressive symptom levels, taking into account demographic, behavioural, and medical differences. These associations do not differ between ethnic groups. Further, β-diversity explains 29%-18% of the ethnic differences in depressive symptoms. Bacterial genera associated with depressive symptoms belong to mulitple families, prominently including the families Christensenellaceae, Lachnospiraceae, and Ruminococcaceae. In summary, the results show that the gut microbiota are linked to depressive symptom levels and that this association generalizes across ethnic groups. Moreover, the results suggest that ethnic differences in the gut microbiota may partly explain parallel disparities in depression.

Cytokines and cecal microbiome modulations conferred by a dual vaccine in Salmonella-infected layers

Zoonotic Salmonella infection is a critical and challenging issue for public health. Since human infections are mainly associated with consuming contaminated chicken products, strategies to reduce Salmonella carriage and shedding are essential. Here we investigate the mechanisms of the live attenuated Salmonella vaccine (AviPro Salmonella Duo) against Salmonella Enteritidis (SE) infection. We focused on inflammatory-related cytokine expressions and cecal microbiota modulations in specific-pathogen-free (SPF) and field layers. Forty-eight 2-day-old SPF layers were randomly allotted into S.SEvc, S.SEc, S.Vc, and S.Ct groups in trial 1. The equal number of filed layers at 25 wk were allocated into SEvc, SEc, Vc, and Ct groups in trial 2. Each group contained 12 layers. Groups were further assigned for vaccination (S.Vc and Vc groups), SE challenge (S.SEc and SEc groups), vaccination and the following SE challenge (S.SEvc and SEvc groups), or the placebo treatment (S.Ct and Ct groups). Cecal tissues and contents of layers on day 14 post-SE-challenges were collected for cytokine mRNA expression and 16S rRNA metagenomic analyses. We found that SE challenges significantly upregulated expressions of IFNγ, IL-1β, IL-12β, and NFκB1A in SPF layers. The vaccine notably counteracted the levels of IFNα, IFNγ, and NFκB1A activated by SE attacks. The vaccination, SE challenge, and their combination did not significantly affect alpha diversities but promoted dissimilarities in microbial communities between groups. Eubacterium_coprostanoligenes and Faecalibacterium_prausnitzii were identified as contributory taxa in the cecal microbiota of SE-challenged and vaccinated SPF layers. A significantly higher abundance of Faecalibacterium_prausnitzii in the ceca further correlated with the vaccination conferred protection against SE infection. In contrast, Oscillibacter_valericigenes and Mediterraneibacter_glycyrrhizinilyticus were featured taxa in Salmonella-infected field layers. Megamonas_hypermegale and Megamonas_rupellensis were identified as featured taxa in vaccinated field layers compared to SE-infected layers. To conclude, applying a dual Salmonella vaccine in this study modulated expressions of inflammatory-related cytokines and the cecal microbiome in layers, contributing to protection against SE infection. The feature microbes are promising for developing predictive indices and as antibiotic alternatives added to feed to reduce the risk of Salmonella shedding and contamination.

Substrate and low intensity fires influence bacterial communities in longleaf pine savanna

Bacterial communities associated with vegetation-soil interfaces have important roles in terrestrial ecosystems. These bacterial communities, studied almost exclusively in unburnt ecosystems or those affected by rare, high-intensity wildfires, have been understudied in fire-frequented grasslands and savannas. The composition of ground-level bacterial communities was explored in an old-growth pine savanna with a centuries-long management history of prescribed fires every 1-2 years. Using 16S metabarcoding, hypotheses were tested regarding differences in bacterial families of litter and soil surface substrates in patches of ground layer vegetation that were naturally burnt or unburnt during landscape-level prescribed fires. Litter/soil substrates and fire/no fire treatments explained 67.5% of bacterial community variation and differences, driven by relative abundance shifts of specific bacterial families. Fires did not strongly affect plant or soil variables, which were not linked to bacterial community differences. Litter/soil substrates and the naturally patchy frequent fires appear to generate microhabitat heterogeneity in this pine savanna, driving responses of bacterial families. Prescribed fire management may benefit from considering how fire-altered substrate heterogeneity influences and maintains microbial diversity and function, especially in these fiery ecosystems. Frequent, low-intensity fires appear ecologically important in maintaining the diverse microbial foundation that underlie ecosystem processes and services in fire-frequented habitats.

Toward a Deeper Understanding of Gut Microbiome in Depression: The Promise of Clinical Applicability

The emergence of the coronavirus disease 2019 pandemic has dramatically increased the global prevalence of depression. Unfortunately, antidepressant drugs benefit only a small minority of patients. Thus, there is an urgent need to develop new interventions. Accumulating evidence supports a causal relationship between gut microbiota dysbiosis and depression. To advance microbiota-based diagnostics and therapeutics of depression, a comprehensive overview of microbial alterations in depression is presented to identify effector microbial biomarkers. This procedure generated 215 bacterial taxa from humans and 312 from animal models. Compared to controls, depression shows significant differences in β-diversity, but no changes in microbial richness and diversity. Additionally, species-specific microbial changes are identified like increased Eggerthella in humans and decreased Acetatifactor in rodent models. Moreover, a disrupted microbiome balance and functional changes, characterized by an enrichment of pro-inflammatory bacteria (e.g., Desulfovibrio and Escherichia/Shigella) and depletion of anti-inflammatory butyrate-producing bacteria (e.g., Bifidobacterium and Faecalibacterium) are consistently shared across species. Confounding effects of geographical region, depression type, and intestinal segments are also investigated. Ultimately, a total of 178 species and subspecies probiotics are identified to alleviate the depressive phenotypes. Current findings provide a foundation for developing microbiota-based diagnostics and therapeutics and advancing microbiota-oriented precision medicine for depression.

Genital Microbiota and Outcome of Assisted Reproductive Treatment-A Systematic Review

The balance between different bacterial species is essential for optimal vaginal health. Microbiome includes the host genome along with microorganism genomes and incorporates the biotic and abiotic factors, reflecting the habitat as a whole. A significant difference exists in the composition and number of the human microbiota in healthy individuals. About one-tenth of the total body microbiota exists in the urogenital tract and these can be identified by microscopy and culture-based methods, quantitative PCR, next generation and whole genome sequencing. The trend of delaying the planning of pregnancy to a later age nowadays has resulted in magnifying the use of assisted reproductive treatment (ART). Hence, genital microbiota and its impact on fertility has generated immense interest in recent years. In this systematic review, we searched the available evidence on the microbiota of the genital tract in women undergoing ART and studied the outcomes of IVF in different microbial compositions. Despite the inconsistency of the studies, it is evident that vaginal, cervical and endometrial microbiota might play a role in predicting ART outcomes. However, there is no clear evidence yet on whether the diversity, richness, quantity, or composition of species in the maternal genital tract significantly affects the outcomes in ARTs.

The microbial community associated with Parascaris spp. infecting juvenile horses

Background

Parasitic nematodes, including large roundworms colloquially known as ascarids, affect the health and well-being of livestock animals worldwide. The equine ascarids, Parascaris spp., are important parasites of juvenile horses and the first ascarids to develop widespread anthelmintic resistance. The microbiota has been shown to be an important factor in the fitness of many organisms, including parasitic nematodes, where endosymbiotic Wolbachia have been exploited for treatment of filariasis in humans.

Methods

This study used short-read 16S rRNA sequences and Illumina sequencing to characterize and compare microbiota of whole worm small intestinal stages and microbiota of male and female intestines and gonads. Diversity metrics including alpha and beta diversity, and the differential abundance analyses DESeq2, ANCOM-BC, corncob, and metagenomeSeq were used for comparisons.

Results

Alpha and beta diversity of whole worm microbiota did not differ significantly between groups, but Simpson alpha diversity was significantly different between female intestine (FI) and male gonad (MG) (P= 0.0018), and Shannon alpha diversity was significantly different between female and male gonads (P = 0.0130), FI and horse jejunum (HJ) (P = 0.0383), and FI and MG (P= 0.0001). Beta diversity (Fig. 2B) was significantly different between female and male gonads (P = 0.0006), male intestine (MI) and FG (P = 0.0093), and MG and FI (P = 0.0041). When comparing organs, Veillonella was differentially abundant for DESeq2 and ANCOM-BC (p < 0.0001), corncob (P = 0.0008), and metagenomeSeq (P = 0.0118), and Sarcina was differentially abundant across four methods (P < 0.0001). Finally, the microbiota of all individual Parascaris spp. specimens were compared to establish shared microbiota between groups.

Conclusions

Overall, this study provided important information regarding the Parascaris spp. microbiota and provides a first step towards determining whether the microbiota may be a viable target for future parasite control options.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05533-y.

Altered gut microbiota correlates with behavioral problems but not gastrointestinal symptoms in individuals with autism

BACKGROUND

Despite inconsistent results across studies, emerging evidence suggests that the microbial micro-environment may be associated with autism spectrum disorder (ASD). Geographical and cultural factors highly impact microbial profiles, and there is a shortage of data from East Asian populations. This study aimed to comprehensively characterize microbial profiles in an East Asian sample and explore whether gut microbiota contributes to clinical symptoms, emotional/behavioral problems, and GI symptoms in ASD.

METHODS

We assessed 82 boys and young men with ASD and 31 typically developing controls (TDC), aged 6-25 years. We analyzed the stool sample of all participants with 16S V3-V4 rRNA sequencing and correlated its profile with GI symptoms, autistic symptoms, and emotional/behavioral problems.

RESULTS

Autistic individuals, compared to TDC, had worse GI symptoms. There were no group differences in alpha diversity of species richness estimates (Shannon-wiener and Simpson diversity indices). Participants with ASD had an increased relative abundance of Fusobacterium, Ruminococcus torques group (at the genus level), and Bacteroides plebeius DSM 17135 (at the species level), while a decreased relative abundance of Ruminococcaceae UCG 013, Ervsipelotrichaceae UCG 003, Parasutterella, Clostridium sensu stricto 1, Turicibacter (at the genus level), and Clostridium spiroforme DSM 1552 and Intestinimonas butyriciproducens (at the species level). Altered taxonomic diversity in ASD significantly correlated with autistic symptoms, thought problems, delinquent behaviors, self dysregulation, and somatic complaints. We did not find an association between gut symptoms and gut microbial dysbiosis.

CONCLUSIONS

Our findings suggest that altered microbiota are associated with behavioral phenotypes but not GI symptoms in ASD. The function of the identified microbial profiles mainly involves the immune pathway, supporting the hypothesis of a complex relationship between altered microbiome, immune dysregulation, and ASD that may advance the discovery of molecular biomarkers for ASD.

Suppression of Methicillin-Resistant Staphylococcus aureus and Reduction of Other Bacteria by Black Soldier Fly Larvae Reared on Potato Substrate

Larvae of black soldier flies, Hermetia illucens, are increasingly used for biological conversion of animal and plant wastes into ingredients of animal feeds on an industrial scale. The presence of pathogenic microorganisms in harvested larvae may be a serious problem for wide-scale adoption of this technology. Fortunately, black soldier fly larvae may have some antimicrobial properties. Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterium associated with various environments that can be pathogenic to humans and farmed animals. We tested whether black soldier fly larvae suppress MRSA on potato substrate. Autoclaved potatoes containing black soldier fly larvae (P+BSFL), potatoes inoculated with MRSA and containing black soldier fly larvae (P+MRSA+BSFL), and potatoes inoculated with MRSA (P+MRSA) were incubated in glass jars. Substrate samples were taken after 3 and 7 days of incubation and plated on Trypticase soy agar (TSA) and Staphylococcus medium 110 agar (SA) to quantify total bacteria and MRSA, respectively. DNA was extracted from potato substrates on both days and sequenced to assess bacterial and fungal diversity using 515F/806R and internal transcribed spacer (ITS) 1/2 primers, respectively, and QIIME 2.0 software. Both total bacterial and MRSA-specific CFU were reduced in the presence of black soldier fly larvae, with a larger reduction for the latter. Twenty-five bacterial genera and 3 fungal genera were detected. Twenty bacterial genera were shared among the treatments and the days, but their relative abundances often varied. Among the most abundant genera, only Enterococcus and Lactococcus were universally present. Our findings confirm antimicrobial properties of black soldier fly larvae. IMPORTANCE Larvae of black soldier flies, Hermetia illucens, may be used to provide an environmentally sustainable and economically viable method for biological conversion of animal and plant wastes into ingredients of animal feeds on an industrial scale. However, contamination of harvested larvae by pathogenic microorganisms inhabiting decaying substrates may be a serious problem for wide-scale adoption of this technology. Fortunately, black soldier fly larvae may have some antimicrobial properties, including suppression of several common pathogens. Our study showed that such a suppression applies to methicillin-resistant Staphylococcus aureus, which is a ubiquitous bacterium pathogenic to animals (including humans).

Gut microbiota and transcriptome analysis reveals a genetic component to dropping moisture in chickens

High dropping moisture (DM) in poultry production has deleterious effects on the environment, feeding cost, and public health of people and animals. To explore the contributing genetic components, we classified DM of 67-wk-old Rhode Island Red (RIR) hens at 4 different levels and evaluated the underlying genetic heritability. We found the heritability of DM to be 0.219, indicating a moderately heritable trait. We then selected chickens with the highest and lowest DM levels. Using transcriptome, we only detected 12 differentially expressed genes (DEGs) between these 2 groups from the spleen, and 1,507 DEGs from intestinal tissues (jejunum and cecum). The low number of DEGs observed in the spleen suggests that differing moisture levels are not attributed to pathogenic infection. Fourteen of the intestinal high expressed genes are associated with water-salt metabolism (WSM). We also investigated the gut microbial composition by 16S rRNA gene amplicon sequencing. Six different microbial operational taxonomic units (OTUs) (Cetobacterium, Sterolibacterium, Elusimicrobium, Roseburia, Faecalicoccus, and Megamonas) between the 2 groups from jejunum and cecum are potentially biomarkers related to DM levels. Our results identify a genetic component to chicken DM, and can guide breeding strategies.

Fecal microbiome alterations in treatment-naive de novo Parkinson's disease

Gut microbiota alterations in Parkinson's disease (PD) have been found in several studies and are suggested to contribute to the pathogenesis of PD. However, previous results could not be adequately adjusted for a potential confounding effect of PD medication and disease duration, as almost all PD participants were already using dopaminergic medication and were included several years after diagnosis. Here, the gut microbiome composition of treatment-naive de novo PD subjects was assessed compared to healthy controls (HC) in two large independent case-control cohorts (n = 136 and 56 PD, n = 85 and 87 HC), using 16S-sequencing of fecal samples. Relevant variables such as technical batches, diet and constipation were assessed for their potential effects. Overall gut microbiome composition differed between PD and HC in both cohorts, suggesting gut microbiome alterations are already present in de novo PD subjects at the time of diagnosis, without the possible confounding effect of dopaminergic medication. Although no differentially abundant taxon could be replicated in both cohorts, multiple short chain fatty acids (SCFA) producing taxa were decreased in PD in both cohorts. In particular, several taxa belonging to the family Lachnospiraceae were decreased in abundance. Fewer taxonomic differences were found compared to previous studies, indicating smaller effect sizes in de novo PD.

Advances in artificial intelligence-based microbiome for PMI estimation

Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.

Improving environmental monitoring of Vibrionaceae in coastal ecosystems through 16S rRNA gene amplicon sequencing

The Vibrionaceae family groups genetically and metabolically diverse bacteria thriving in all marine environments. Despite often representing a minor fraction of bacterial assemblages, members of this family can exploit a wide variety of nutritional sources, which makes them important players in biogeochemical dynamics. Furthermore, several Vibrionaceae species are well-known pathogens, posing a threat to human and animal health. Here, we applied the phylogenetic placement coupled with a consensus-based approach using 16S rRNA gene amplicon sequencing, aiming to reach a reliable and fine-level Vibrionaceae characterization and identify the dynamics of blooming, ecologically important, and potentially pathogenic species in different sites of the northern Adriatic Sea. Water samples were collected monthly at a Long-Term Ecological Research network site from 2018 to 2021, and in spring and summer of 2019 and 2020 at two sites affected by depurated sewage discharge. The 41 identified Vibrionaceae species represented generally below 1% of the sampled communities; blooms (up to ~ 11%) mainly formed by Vibrio chagasii and Vibrio owensii occurred in summer, linked to increasing temperature and particulate matter concentration. Pathogenic species such as Vibrio anguilllarum, Vibrio tapetis, and Photobacterium damselae were found in low abundance. Depuration plant samples were characterized by a lower abundance and diversity of Vibrionaceae species compared to seawater, highlighting that Vibrionaceae dynamics at sea are unlikely to be related to wastewater inputs. Our work represents a further step to improve the molecular approach based on short reads, toward a shared, updated, and curated phylogeny of the Vibrionaceae family.

Differences in Supragingival Microbiome in Patients with and without Full-Crown Prostheses

Objectives: To characterize the microflora profile of supragingival biofilm in patients with and without full-crown prostheses. Methods: Plaque samples of full-crown prostheses and teeth in patients with porcelain-fused-to-metal crowns, all-ceramic crowns, and no prostheses were collected (three patients per group), using 16S rRNA high-throughput sequencing technology to conduct DNA sequencing on the samples and using Qiime, R, and PICRUSt2 software to perform bioinformatics analyses and functional analyses on sequencing data. Results: In total, 110,209 valid sequences were obtained in the experiment, corresponding to 11 phyla and 120 genera. The predominant species shared by the three groups were phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria and genera Rothia, Porphyromonas, Prevotella, Streptococcus, Veillonella, Leptotrichia, Neisseria, Citrobacter, and Pseudomonas. The species-difference analysis showed that genus Hameophilus significantly increased after the patient wore the dental prosthesis. Compared with the no-prosthesis samples, the functional analysis showed that cell motility increased in the samples from full-crown prostheses, while replication and repair, and translation decreased. Conclusions: This study reveals the changes in the oral microbial community of patients with full-crown prostheses, which could provide insights regarding the safety of materials for long-term use in the oral cavity.