OTUs and ASVs Produce Comparable Taxonomic and Diversity from Shrimp Microbiota 16S Profiles Using Tailored Abundance Filters

New insights into biologic interpretation of bioinformatic pipelines for fish eDNA metabarcoding: A case study in Pearl River estuary

Environmental DNA (eDNA) metabarcoding is an emerging tool for monitoring biological communities in aquatic ecosystems. The selection of bioinformatic pipelines significantly impacts the results of biodiversity assessments. However, there is currently no consensus on the appropriate bioinformatic pipelines for fish community analysis in eDNA metabarcoding. In this study, we compared three bioinformatic pipelines (Uparse, DADA2, and UNOISE3) using real and mock (constructed with 15/30 known fish) communities to investigate the differences in biological interpretation during the data analysis process in eDNA metabarcoding. Performance evaluation and diversity analyses revealed that the choice of bioinformatic pipeline could impact the biological results of metabarcoding experiments. Among the three pipelines, the operational taxonomic units (OTU)-based pipeline (Uparse) showed the best performance (sensitivity: 0.6250 ± 0.0166; compositional similarity: 0.4000 ± 0.0571), the highest richness (25-102) and minimal inter-group differences in alpha diversity. It suggested the OTU-based pipeline possessed superior capability in fish diversity monitoring compared to ASV/ZOTU-based pipeline. Additionally, the Bray-Curtis distance matrix achieved the highest discriminative effect in the PCoA (43.3%-53.89%) and inter-group analysis (P < 0.01), indicating it was better at distinguishing compositional differences or specific genera of fish community at different sampling sites than other distance matrices. These findings provide new insights into fish community monitoring through eDNA metabarcoding in estuarine environments.

Unearthing Lactococcus lactis and Scheffersomyeces symbionts from edible wood-boring beetle larvae as a bio-resource for industrial applications

BACKGROUND

Gut microbiota have several advantages in influencing the host nutrition, metabolism, immunity and growth. However, the understanding of the gut microbiota in key edible wood-boring beetle larvae remain largely undefined. In the present study, the characteristics of the gut microbiota of two edible wood-boring species (Titocerus jaspideus and Passalus punctiger) from two indigenous forested areas were investigated.

RESULTS

Over 50% of Amplicon Sequence Variants (ASVs) constituted of Firmicutes in T. jaspideus. The dominant phyla in both beetle species were Bacteroidota (4.20-19.79%) and Proteobacteria (15.10-23.90%). Lactococcus lactis was the most abundant and core prokaryote in the guts of T. jaspideus. The fungi identified in the gut of both insects belong to the phylum Obazoa (66%) and Ascomycota (> 15%). Scheffersomyeces sp. was the core eukaryote recorded. The diversity of gut microbiota in both insect species did not vary significantly. Most of the prokaryotic genes expressed were predominantly associated with biosynthesis and metabolism.

CONCLUSION

Our findings demonstrated that Lactococcus lactis and Scheffersomyeces are core gut microbes of wood boring beetle larvae with desirable probiotic properties and promising use in food product fermentation for improved growth performance, gut barrier health, intestinal flora balance and immune protection for human and animals. Further studies to highlight the latest medical-based applications of L. lactis as live-delivery vector for the administration of therapeutics against both communicable and non-communicable diseases are warranted.

Transforming gastrointestinal helminth parasite identification in vertebrate hosts with metabarcoding: a systematic review

BACKGROUND

Gastrointestinal helminths are a very widespread group of intestinal parasites that can cause major health issues in their hosts, including severe illness or death. Traditional methods of helminth parasite identification using microscopy are time-consuming and poor in terms of taxonomic resolution, and require skilled observers. DNA metabarcoding has emerged as a powerful alternative for assessing community composition in a variety of sample types over the last few decades. While metabarcoding approaches have been reviewed for use in other research areas, the use of metabarcoding for parasites has only recently become widespread. As such, there is a need to synthesize parasite metabarcoding methodology and highlight the considerations to be taken into account when developing a protocol.

METHODS

We reviewed published literature that utilized DNA metabarcoding to identify gastrointestinal helminth parasites in vertebrate hosts. We extracted information from 62 peer-reviewed papers published between 2014 and 2023 and created a stepwise guide to the metabarcoding process.

RESULTS

We found that studies in our review varied in technique and methodology, such as the sample type utilized, genetic marker regions targeted and bioinformatic databases used. The main limitations of metabarcoding are that parasite abundance data may not be reliably attained from sequence read numbers, metabarcoding data may not be representative of the species present in the host and the cost and bioinformatic expertise required to utilize this method may be prohibitive to some groups.

CONCLUSIONS

Overall, using metabarcoding to assess gastrointestinal parasite communities is preferable to traditional methods, yielding higher taxonomic resolution, higher throughput and increased versatility due to its utility in any geographical location, with a variety of sample types, and with virtually any vertebrate host species. Additionally, metabarcoding has the potential for exciting new discoveries regarding host and parasite evolution.

Characterising the Tasmanian devil (Sarcophilus harrisii) pouch microbiome in lactating and non-lactating females

Wildlife harbour a diverse range of microorganisms that affect their health and development. Marsupials are born immunologically naïve and physiologically underdeveloped, with primary development occurring inside a pouch. Secretion of immunological compounds and antimicrobial peptides in the epithelial lining of the female's pouch, pouch young skin, and through the milk, are thought to boost the neonate's immune system and potentially alter the pouch skin microbiome. Here, using 16S rRNA amplicon sequencing, we characterised the Tasmanian devil pouch skin microbiome from 25 lactating and 30 non-lactating wild females to describe and compare across these reproductive stages. We found that the lactating pouch skin microbiome had significantly lower amplicon sequence variant richness and diversity than non-lactating pouches, however there was no overall dissimilarity in community structure between lactating and non-lactating pouches. The top five phyla were found to be consistent between both reproductive stages, with over 85% of the microbiome being comprised of Firmicutes, Proteobacteria, Fusobacteriota, Actinobacteriota, and Bacteroidota. The most abundant taxa remained consistent across all taxonomic ranks between lactating and non-lactating pouch types. This suggests that any potential immunological compounds or antimicrobial peptide secretions did not significantly influence the main community members. Of the more than 16,000 total identified amplicon sequence variants, 25 were recognised as differentially abundant between lactating and non-lactating pouches. It is proposed that the secretion of antimicrobial peptides in the pouch act to modulate these microbial communities. This study identifies candidate bacterial clades on which to test the activity of Tasmanian devil antimicrobial peptides and their role in pouch young protection, which in turn may lead to future therapeutic development for human diseases.

Synthesis of current pediatric urinary microbiome research

The human urinary bladder hosts a complex microbial community of low biomass referred to as the urobiome. While the composition of the urobiome has been investigated in adults for over a decade now, only a few studies have considered the presence and composition of the urobiome in children. It is critical to explore how the urobiome develops throughout the life span and how it changes in the presence of various health conditions. Therefore, we set to review the available data on pediatric urobiome composition and its development with age and disease. In addition, we focused on identifying and reporting specific gaps in our knowledge of the pediatric urobiome that we hope will be addressed by future studies in this swiftly developing field with fast-improving methods and consensus.

High-throughput sequencing-based analysis of the composition and diversity of the endophytic bacterial community in the roots of Dipsacus asperoides

This study employed Illumina high-throughput sequencing technology to investigate diversity and community structure of endophytic bacteria in wild D. asperoides growing in three distinct regions. The study analyzed the impact of region on endophytic bacteria, uncovered the core bacterial community, and furnished valuable insights for the screening of endophytic bacteria. This study identified 6,540 amplicon sequence variants (ASVs) coexisting with D. asperoides roots. These ASVs belong to 35 phyla, 84 classes, 204 orders, 365 families, and 708 genera. At the phylum level, the dominant phyla were Proteobacteria and Actinobacteria, while at the genus level, Acidothermus, Acidibacter, Bradyrhizobium, Frankia, and Pseudomonas emerged as the dominant genera. Furthermore, noticeable differences in endophytic bacterial communities were observed between the Yunnan and Guizhou regions. These findings can serve as a reference for the authentication of medicinal materials from various origins and the selection of active strains.

A new method for examining the co-occurrence network of fossil assemblages

Currently, studies of ancient faunal community networks have been based mostly on uniformitarian and functional morphological evidence. As an important source of data, taphonomic evidence offers the opportunity to provide a broader scope for understanding palaeoecology. However, palaeoecological research methods based on taphonomic evidence are relatively rare, especially for body fossils in lacustrine sediments. Such fossil communities are not only affected by complex transportation and selective destruction in the sedimentation process, they also are strongly affected by time averaging. Historically, it has been believed that it is difficult to study lacustrine entombed fauna by a small-scale quadrat survey. Herein, we developed a software, the TaphonomeAnalyst, to study the associational network of lacustrine entombed fauna, or taphocoenosis. TaphonomeAnalyst allows researchers to easily perform exploratory analyses on common abundance profiles from taphocoenosis data. The dataset for these investigations resulted from fieldwork of the latest Middle Jurassic Jiulongshan Formation near Daohugou Village, in Ningcheng County of Inner Mongolia, China, spotlighting the core assemblage of the Yanliao Fauna. Our data included 27,000 fossil specimens of animals from this deposit, the Yanliao Fauna, whose analyses reveal sedimentary environments, taphonomic conditions, and co-occurrence networks of this highly studied assemblage, providing empirically robust and statistically significant evidence for multiple Yanliao habitats.

Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis

The multi-batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision-making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene-derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome-based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome-specific methods for accounting for or correcting them.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.

Planktonic and epilithic prokaryota community compositions in a large temperate river reflect climate change related seasonal shifts

In freshwaters, microbial communities are of outstanding importance both from ecological and public health perspectives, however, they are threatened by the impact of global warming. To reveal how different prokaryotic communities in a large temperate river respond to environment conditions related to climate change, the present study provides the first detailed insight into the composition and spatial and year-round temporal variations of planktonic and epilithic prokaryotic community. Microbial diversity was studied using high-throughput next generation amplicon sequencing. Sampling was carried out monthly in the midstream and the littoral zone of the Danube, upstream and downstream from a large urban area. Result demonstrated that river habitats predominantly determine the taxonomic composition of the microbiota; diverse and well-differentiated microbial communities developed in water and epilithon, with higher variance in the latter. The composition of bacterioplankton clearly followed the prolongation of the summer resulting from climate change, while the epilithon community was less responsive. Rising water temperatures was associated with increased abundances of many taxa (such as phylum Actinobacteria, class Gammaproteobacteria and orders Synechococcales, Alteromonadales, Chitinophagales, Pseudomonadales, Rhizobiales and Xanthomonadales), and the composition of the microbiota also reflected changes of several further environmental factors (such as turbidity, TOC, electric conductivity, pH and the concentration of phosphate, sulphate, nitrate, total nitrogen and the dissolved oxygen). The results indicate that shift in microbial community responding to changing environment may be of crucial importance in the decomposition of organic compounds (including pollutants and xenobiotics), the transformation and accumulation of heavy metals and the occurrence of pathogens or antimicrobial resistant organisms.

Microbial Diversity and Functional Potential of Keem: A Traditional Starter Culture for Alcoholic Beverage-Application of Next-Generation Amplicon and Shotgun Metagenome Sequences

"Pakhoi" is an ethnic drink of the Tons valley, Uttarakhand, India produced by fermenting jaggery and barley with the help of a starter culture called "keem". In the present study, we investigated the microbial diversity and associated functional potential of "keem" using shotgun metagenome sequencing and amplicon sequencing. We also compared the taxonomic data obtained using these two sequencing techniques. The results showed that shotgun sequencing revealed a higher resolution of taxonomic profiling as compared to the amplicon sequencing. Furthermore, it was found that the genera detected by shotgun sequencing were valuable for facilitating the fermentation process. Additionally, to understand the functional profiling of the genera, different databases were used for annotation, resulting in a total of 13 metabolic pathways. The five most abundant KEGG functions were genetic information processing, metabolism, translation, cofactor and vitamin metabolism and xenobiotic degradation. In contrast, the top five COG were in order of highest frequency sequences belonging to transcription, followed by general function prediction, carbohydrate transport metabolism, amino acid transport and metabolism and translation and biogenesis. Gene ontology revealed many pathways, biochemical processes and molecular functions associated with the organisms forming the starter culture. Overall, the present study can help to understand the microbial diversity and its role in fermentation of traditional alcoholic beverages using "Keem".

The Effect of the Microalgae Chlorella vulgaris on the Gut Microbiota of Juvenile Nile Tilapia (Oreochromis niloticus) Is Feeding-Time Dependent

Chlorella vulgaris is one of the most commonly used microalgae in aquaculture feeds. It contains high concentrations of various kinds of nutritional elements that are involved in the physiological regulation of aquaculture animals. However, few studies have been conducted to illustrate their influence on the gut microbiota in fish. In this work, the gut microbiota of Nile tilapia (Oreochromis niloticus) (average weight is 6.64 g) was analyzed by high-throughput sequencing of the 16S rRNA gene after feeding with 0.5% and 2% C. vulgaris additives in diets for 15 and 30 days (average water temperature was 26 °C). We found that the impact of C. vulgaris on the gut microbiota of Nile tilapia was feeding-time dependent. Only by feeding for 30 days (not 15 days) did the addition of 2% C. vulgaris to diets significantly elevate the alpha diversity (Chao1, Faith pd, Shannon, Simpson, and the number of observed species) of the gut microbiota. Similarly, C. vulgaris exerted a significant effect on the beta diversity (Bray-Curtis similarity) of the gut microbiota after feeding for 30 days (not 15 days). During the 15-day feeding trial, LEfSe analysis showed that Paracoccus, Thiobacillus, Dechloromonas, and Desulfococcus were enriched under 2% C. vulgaris treatment. During the 30-day feeding trial, Afipia, Ochrobactrum, Polymorphum, Albidovulum, Pseudacidovorax, and Thiolamprovum were more abundant in 2% C. vulgaris-treated fish. C. vulgaris promoted the interaction of gut microbiota in juvenile Nile tilapia by increasing the abundance of Reyranella. Moreover, during the feeding time of 15 days, the gut microbes interacted more closely than those during the feeding time of 30 days. This work will be valuable for understanding how C. vulgaris in diets impacts the gut microbiota in fish.

Composition, structure, and functional shifts of prokaryotic communities in response to co-composting of various nitrogenous green feedstocks

BACKGROUND

Thermophilic composting is a promising method of sanitizing pathogens in manure and a source of agriculturally important thermostable enzymes and microorganisms from organic wastes. Despite the extensive studies on compost prokaryotes, shifts in microbial profiles under the influence of various green materials and composting days are still not well understood, considering the complexity of the green material sources. Here, the effect of regimens of green composting material on the diversity, abundance, and metabolic capacity of prokaryotic communities in a thermophilic compost environment was examined.

METHODS

Total community 16S rRNA was recovered from triplicate compost samples of Lantana-based, Tithonia-based, Grass-based, and mixed (Lantana + Tithonia + Grass)- based at 21, 42, 63, and 84 days of composting. The 16S rRNA was sequenced using the Illumina Miseq platform. Bioinformatics analysis was done using Divisive Amplicon Denoising Algorithm version 2 (DADA2) R version 4.1 and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States version 2 (PICRUSt2) pipelines for community structure and metabolic profiles, respectively. In DADA2, prokaryotic classification was done using the Refseq-ribosomal database project (RDP) and SILVA version 138 databases.

RESULTS

Our results showed apparent differences in prokaryotic community structure for total diversity and abundance within the four compost regimens and composting days. The study showed that the most prevalent phyla during composting included Acidobacteriota, Actinobacteriota, Bacteroidota, Chloroflexi, and Proteobacteria. Additionally, there were differences in the overall diversity of metabolic pathways but no significant differences among the various compost treatments on major metabolic pathways like carbohydrate biosynthesis, carbohydrate degradation, and nitrogen biosynthesis.

CONCLUSION

Various sources of green material affect the succession of compost nutrients and prokaryotic communities. The similarity of amounts of nutrients, such as total Nitrogen, at the end of the composting process, despite differences in feedstock material, indicates a significant influence of composting days on the stability of nutrients during composting.

Benchmarking and Validation of a Bioinformatics Workflow for Meat Species Identification Using 16S rDNA Metabarcoding

DNA-metabarcoding is becoming more widely used for routine authentication of meat-based food and feed products. Several methods validating species identification methods through amplicon sequencing have already been published. These use a variety of barcodes and analysis workflows, however, no methodical comparison of available algorithms and parameter optimization are published hitherto for meat-based products' authenticity. Additionally, many published methods use very small subsets of the available reference sequences, thereby limiting the potential of the analysis and leading to over-optimistic performance estimates. We here predict and compare the ability of published barcodes to distinguish taxa in the BLAST NT database. We then use a dataset of 79 reference samples, spanning 32 taxa, to benchmark and optimize a metabarcoding analysis workflow for 16S rDNA Illumina sequencing. Furthermore, we provide recommendations as to the parameter choices, sequencing depth, and thresholds that should be used to analyze meat metabarcoding sequencing experiments. The analysis workflow is publicly available, and includes ready-to-use tools for validation and benchmarking.

Geography, taxonomy, and ecological guild: Factors impacting freshwater macroinvertebrate gut microbiomes

Despite their diversity, global distribution, and apparent effects on host biology, the rules of life that govern variation in microbiomes among host species remain unclear, particularly in freshwater organisms. In this study, we sought to assess whether geographic location, taxonomy (order, family, and genus), or functional feeding group (FFG) designations would best explain differences in the gut microbiome composition among macroinvertebrates sampled across 10 National Ecological Observatory Network's (NEON) freshwater stream sites in the United States. Subsequently, we compared the beta diversity of microbiomes among locations, taxonomy (order, family, and genus), and FFGs in a single statistical model to account for variation within the source microbial community and the types of macroinvertebrates sampled across locations. We determined significant differences in community composition among macroinvertebrate orders, families, genera, and FFGs. Differences in microbiome compositions were underscored by different bacterial ASVs that were differentially abundant among variables (four bacterial ASVs across the 10 NEON sites, 43 ASVs among the macroinvertebrate orders, and 18 bacterial ASVs differing among the five FFGs). Analyses of variations in microbiome composition using the Bray-Curtis distance matric revealed FFGs as the dominant source of variation (mean standard deviation of 0.8), followed by stream site (mean standard deviation of 0.5), and finally family and genus (mean standard deviation of 0.3 each). Our findings revealed a principal role for FFG classification in insect gut microbiome beta diversity with additional roles for geographic distribution and taxonomy.

Differences in the subgingival microbiome according to stage of periodontitis: A comparison of two geographic regions

No microbiological criteria were included in the 2018 EFP-AAP classification of periodontal diseases that could be used to differentiate between stages and grades. Furthermore, differences in the subgingival microbiome depending on stage and grade have not been established. Sixty subgingival biofilm samples were collected in Spain (n = 30) and Colombia (n = 30) from three distinct patient categories: those with periodontal health/gingivitis (n = 20), those with stage I-II periodontitis (n = 20), and those with stage III-IV periodontitis (n = 20). Patients were evaluated by 16S rRNA gene amplification sequencing. Amplicon sequence variants were used to assign taxonomic categories compared to the Human Oral Microbiome Database (threshold ≥97% identity). Alpha diversity was established by Shannon and Simpson indices, and principal coordinate analysis, ANOSIM, and PERMANOVA of the UNIFRAC distances were performed using QIIME2. Although differences in the alpha diversity were observed between samples according to country, Filifactor alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Fretibacterium fastidiosum, Lachnospiraceae [G-8] bacterium HMT 500, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, Peptostreptococcus stomatis, and Tannerella forsythia were associated with periodontitis sites in all stages. However, only F. alocis, Peptostreptococcaceae [XI][G-4] bacterium HMT 369, Peptostreptococcaceae [XI][G-9] [Eubacterium] brachy, Peptostreptococcaceae [XI][G-5] [Eubacterium] saphenum, and Desulfobulbus sp. HMT 041 were consistent in stage III-IV periodontitis in both countries. Porphyromonas gingivalis and Tannerella forsythia were differentially expressed in severe lesions in the countries studied. Although some non-cultivable microorganisms showed differential patterns between the different stages of periodontitis, they were not the same in the two countries evaluated. Further studies using larger samples with advanced next-generation techniques for high-throughput sequencing of phyla and non-cultivable bacteria within the subgingival microbiome could provide more insight into the differences between stages of periodontitis.

Life barcoded by DNA barcodes

The modern concept of DNA-based barcoding for cataloguing biodiversity was proposed in 2003 by first adopting an approximately 600 bp fragment of the mitochondrial COI gene to compare via nucleotide alignments with known sequences from specimens previously identified by taxonomists. Other standardized regions meeting barcoding criteria then are also evolving as DNA barcodes for fast, reliable and inexpensive assessment of species composition across all forms of life, including animals, plants, fungi, bacteria and other microorganisms. Consequently, global DNA barcoding campaigns have resulted in the formation of many online workbenches and databases, such as BOLD system, as barcode references, and facilitated the development of mini-barcodes and metabarcoding strategies as important extensions of barcode techniques. Here we intend to give an overview of the characteristics and features of these barcode markers and major reference libraries existing for barcoding the planet’s life, as well as to address the limitations and opportunities of DNA barcodes to an increasingly broader community of science and society.

Ecological Observations Based on Functional Gene Sequencing Are Sensitive to the Amplicon Processing Method

Until recently, the de facto method for short-read-based amplicon reconstruction was a sequence similarity threshold approach (operational taxonomic units [OTUs]). This has changed with the amplicon sequence variant (ASV) method where distributions are fitted to abundance profiles of individual genes using a noise-error model. While OTU-based approaches are still useful for 16S rRNA/18S rRNA genes, where thresholds of 97% to 99% are used, their use for functional genes is still debatable as there is no consensus on clustering thresholds. Here, we compare OTU- and ASV-based reconstruction approaches and taxonomy assignment methods, the naive Bayesian classifier (NBC) and Bayesian lowest common ancestor (BLCA) algorithm, using a functional gene data set from the microbial nitrogen-cycling community in the Brouage mudflat (France). A range of OTU similarity thresholds and ASVs were used to compare amoA (ammonia-oxidizing archaea [AOA] and ammonia-oxidizing bacteria [AOB]), nxrB, nirS, nirK, and nrfA communities between differing sedimentary structures. Significant effects of the sedimentary structure on weighted UniFrac (WUniFrac) distances were observed for AOA amoA when using ASVs, an OTU at a threshold of 97% sequence identity (OTU-97%), and OTU-85%; AOB amoA when using OTU-85%; and nirS when using ASV, OTU-90%, and OTU-85%. For AOB amoA, significant effects of the sedimentary structures on UniFrac distances were observed when using OTU-97% but not ASVs, and the inverse was found for nrfA. Interestingly, conclusions drawn for nirK and nxrB were consistent between amplicon reconstruction methods. We also show that when the sequences in the reference database are related to the environment in question, the BLCA algorithm leads to more phylogenetically relevant classifications. However, when the reference database contains sequences more dissimilar to the ones retrieved, the NBC obtains more information. IMPORTANCE Several analysis pipelines are available to microbial ecologists to process amplicon sequencing data, yet to date, there is no consensus as to the most appropriate method, and it becomes more difficult for genes that encode a specific function (functional genes). Standardized approaches need to be adopted to increase the reliability and reproducibility of environmental amplicon-sequencing-based data sets. In this paper, we argue that the recently developed ASV approach offers a better opportunity to achieve such standardization than OTUs for functional genes. We also propose a comprehensive framework for quality filtering of the sequencing reads based on protein sequence verification.

Quantitative and analytical tools to analyze the spatiotemporal population dynamics of microbial consortia

Microorganisms occupy almost every niche on earth. They play critical roles in maintaining ecological balance, atmospheric C/N cycle, and human health. Microbes live in consortia with metabolite exchange or signal communication. Quantitative and analytical tools are becoming increasingly important to study microbial consortia dynamics. We argue that a combined reductionist and holistic approach will be important to understanding the assembly rules and spatiotemporal population dynamics of the microbial community (MICOM). Reductionism allows us to reconstruct complex MICOM from isolated or simple synthetic consortia. Holism allows us to understand microbes as a community with cooperation and competition. Here we review the recent development of quantitative and analytical tools to uncover the underlying principles in microbial communities that govern their spatiotemporal change and interaction dynamics. Mathematical models and analytical tools will continue to provide essential knowledge and expand our capability to manipulate and control microbial consortia.

Ranking the biases: The choice of OTUs vs. ASVs in 16S rRNA amplicon data analysis has stronger effects on diversity measures than rarefaction and OTU identity threshold

Advances in the analysis of amplicon sequence datasets have introduced a methodological shift in how research teams investigate microbial biodiversity, away from sequence identity-based clustering (producing Operational Taxonomic Units, OTUs) to denoising methods (producing amplicon sequence variants, ASVs). While denoising methods have several inherent properties that make them desirable compared to clustering-based methods, questions remain as to the influence that these pipelines have on the ecological patterns being assessed, especially when compared to other methodological choices made when processing data (e.g. rarefaction) and computing diversity indices. We compared the respective influences of two widely used methods, namely DADA2 (a denoising method) vs. Mothur (a clustering method) on 16S rRNA gene amplicon datasets (hypervariable region v4), and compared such effects to the rarefaction of the community table and OTU identity threshold (97% vs. 99%) on the ecological signals detected. We used a dataset comprising freshwater invertebrate (three Unionidae species) gut and environmental (sediment, seston) communities sampled in six rivers in the southeastern USA. We ranked the respective effects of each methodological choice on alpha and beta diversity, and taxonomic composition. The choice of the pipeline significantly influenced alpha and beta diversities and changed the ecological signal detected, especially on presence/absence indices such as the richness index and unweighted Unifrac. Interestingly, the discrepancy between OTU and ASV-based diversity metrics could be attenuated by the use of rarefaction. The identification of major classes and genera also revealed significant discrepancies across pipelines. Compared to the pipeline's effect, OTU threshold and rarefaction had a minimal impact on all measurements.

In-Silico Detection of Oral Prokaryotic Species With Highly Similar 16S rRNA Sequence Segments Using Different Primer Pairs

Although clustering by operational taxonomic units (OTUs) is widely used in the oral microbial literature, no research has specifically evaluated the extent of the limitations of this sequence clustering-based method in the oral microbiome. Consequently, our objectives were to: 1) evaluate in-silico the coverage of a set of previously selected primer pairs to detect oral species having 16S rRNA sequence segments with ≥97% similarity; 2) describe oral species with highly similar sequence segments and determine whether they belong to distinct genera or other higher taxonomic ranks. Thirty-nine primer pairs were employed to obtain the in-silico amplicons from the complete genomes of 186 bacterial and 135 archaeal species. Each fasta file for the same primer pair was inserted as subject and query in BLASTN for obtaining the similarity percentage between amplicons belonging to different oral species. Amplicons with 100% alignment coverage of the query sequences and with an amplicon similarity value ≥97% (ASI97) were selected. For each primer, the species coverage with no ASI97 (SC-NASI97) was calculated. Based on the SC-NASI97 parameter, the best primer pairs were OP_F053-KP_R020 for bacteria (region V1-V3; primer pair position for Escherichia coli J01859.1: 9-356); KP_F018-KP_R002 for archaea (V4; undefined-532); and OP_F114-KP_R031 for both (V3-V5; 340-801). Around 80% of the oral-bacteria and oral-archaea species analyzed had an ASI97 with at least one other species. These very similar species play different roles in the oral microbiota and belong to bacterial genera such as Campylobacter, Rothia, Streptococcus and Tannerella, and archaeal genera such as Halovivax, Methanosarcina and Methanosalsum. Moreover, ~20% and ~30% of these two-by-two similarity relationships were established between species from different bacterial and archaeal genera, respectively. Even taxa from distinct families, orders, and classes could be grouped in the same possible OTU. Consequently, regardless of the primer pair used, sequence clustering with a 97% similarity provides an inaccurate description of oral-bacterial and oral-archaeal species, which can greatly affect microbial diversity parameters. As a result, OTU clustering conditions the credibility of associations between some oral species and certain health and disease conditions. This significantly limits the comparability of the microbial diversity findings reported in oral microbiome literature.

Quantifying the Importance of Abiotic and Biotic Factors Governing the Succession of Gut Microbiota Over Shrimp Ontogeny

Intensive studies have evaluated abiotic factors in shaping host gut microbiota. In contrast, little is known on how and to what extent abiotic (geochemical variables) and biotic (i.e., surrounding microbes, younger shrimp, and age) factors assemble the gut microbiota over shrimp ontogeny. Considering the functional importance of gut microbiota in improving host fitness, this knowledge is fundamental to sustain a desirable gut microbiota for a healthy aquaculture. Here, we characterized the successional rules of both the shrimp gut and rearing water bacterial communities over the entire shrimp farming. Both the gut and rearing water bacterial communities exhibited the time decay of similarity relationship, with significantly lower temporal turnover rate for the gut microbiota, which were primarily governed by shrimp age (days postlarval inoculation) and water pH. Gut commensals were primary sourced (averaged 60.3%) from their younger host, rather than surrounding bacterioplankton (19.1%). A structural equation model revealed that water salinity, pH, total phosphorus, and dissolve oxygen directly governed bacterioplankton communities but not for the gut microbiota. In addition, shrimp gut microbiota did not simply mirror the rearing bacterioplankton communities. The gut microbiota tended to be governed by variable selection over shrimp ontogeny, while the rearing bacterioplankton community was shaped by homogeneous selection. However, the determinism of rare and stochasticity of abundant subcommunities were consistent between shrimp gut and rearing water. These findings highlight the importance of independently interpreting host-associated and free-living communities, as well as their rare and abundant subcommunities for a comprehensive understanding of the ecological processes that govern microbial successions.

Refinement of microbiota analysis of specimens from patients with respiratory infections using next-generation sequencing

Next-generation sequencing (NGS) technologies have been applied in bacterial flora analysis. However, there is no standardized protocol, and the optimal clustering threshold for estimating bacterial species in respiratory infection specimens is unknown. This study was conducted to investigate the optimal threshold for clustering 16S ribosomal RNA gene sequences into operational taxonomic units (OTUs) by comparing the results of NGS technology with those of the Sanger method, which has a higher accuracy of sequence per single read than NGS technology. This study included 45 patients with pneumonia with aspiration risks and 35 patients with lung abscess. Compared to Sanger method, the concordance rates of NGS technology (clustered at 100%, 99%, and 97% homology) with the predominant phylotype were 78.8%, 71.3%, and 65.0%, respectively. With respect to the specimens dominated by the Streptococcus mitis group, containing several important causative agents of pneumonia, Bray Curtis dissimilarity revealed that the OTUs obtained at 100% clustering threshold (versus those obtained at 99% and 97% thresholds; medians of 0.35, 0.69, and 0.71, respectively) were more similar to those obtained by the Sanger method, with statistical significance (p < 0.05). Clustering with 100% sequence identity is necessary when analyzing the microbiota of respiratory infections using NGS technology.

Colorectal Cancer Stage-Specific Fecal Bacterial Community Fingerprinting of the Taiwanese Population and Underpinning of Potential Taxonomic Biomarkers

Despite advances in the characterization of colorectal cancer (CRC), it still faces a poor prognosis. There is growing evidence that gut microbiota and their metabolites potentially contribute to the development of CRC. Thus, microbial dysbiosis and their metabolites associated with CRC, based on stool samples, may be used to advantage to provide an excellent opportunity to find possible biomarkers for the screening, early detection, prevention, and treatment of CRC. Using 16S rRNA amplicon sequencing coupled with statistical analysis, this study analyzed the cause–effect shift of the microbial taxa and their metabolites that was associated with the fecal gut microbiota of 17 healthy controls, 21 polyps patients, and 21 cancer patients. The microbial taxonomic shift analysis revealed striking differences among the healthy control, polyps and cancer groups. At the phylum level, Synergistetes was reduced significantly in the polyps group compared to the healthy control and cancer group. Additionally, at the genus level and in association with the cancer group, a total of 12 genera were highly enriched in abundance. In contrast, only Oscillosprira was significantly higher in abundance in the healthy control group. Comparisons of the polyps and cancer groups showed a total of 18 significantly enriched genera. Among them, 78% of the genera associated with the cancer group were in higher abundance, whereas the remaining genera showed a higher abundance in the polyps group. Additionally, the comparison of healthy control and polyp groups showed six significantly abundant genera. More than 66% of these genera showed a reduced abundance in the polyps group than in healthy controls, whereas the remaining genera were highly abundant in the polyps group. Based on tumor presence and absence, the abundance of Olsenella and Lactobacillus at the genus level was significantly reduced in the patient group compared to healthy controls. The significant microbial function prediction revealed an increase in the abundance of metabolites in the polyps and cancer groups compared to healthy controls. A correlation analysis revealed a higher contribution of Dorea in the predicted functions. This study showed dysbiosis of gut microbiota at the taxonomic level and their metabolic functions among healthy subjects and in two stages of colorectal cancer, including adenoma and adenocarcinoma, which might serve as potential biomarkers for the early diagnosis and treatment of CRC.