Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake

Host Genetic Background and Gut Microbiota Contribute to Differential Metabolic Responses to Fructose Consumption in Mice

BACKGROUND

It is unclear how high fructose consumption induces disparate metabolic responses in genetically diverse mouse strains.

OBJECTIVE

We aimed to investigate whether the gut microbiota contributes to differential metabolic responses to fructose.

METHODS

Eight-week-old male C57BL/6J (B6), DBA/2J (DBA), and FVB/NJ (FVB) mice were given 8% fructose solution or regular water (control) for 12 wk. The gut microbiota composition in cecum and feces was analyzed using 16S ribosomal DNA sequencing, and permutational multivariate ANOVA (PERMANOVA) was used to compare community across mouse strains, treatments, and time points. Microbiota abundance was correlated with metabolic phenotypes and host gene expression in hypothalamus, liver, and adipose tissues using Biweight midcorrelation. To test the causal role of the gut microbiota in determining fructose response, we conducted fecal transplants from B6 to DBA mice and vice versa for 4 wk, as well as gavaged antibiotic-treated DBA mice with Akkermansia for 9 wk, accompanied with or without fructose treatment.

RESULTS

Compared with B6 and FVB, DBA mice had significantly higher Firmicutes to Bacteroidetes ratio and lower baseline abundance of Akkermansia and S24-7 (P < 0.05), accompanied by metabolic dysregulation after fructose consumption. Fructose altered specific microbial taxa in individual mouse strains, such as a 7.27-fold increase in Akkermansia in B6 and 0.374-fold change in Rikenellaceae in DBA (false discovery rate <5%), which demonstrated strain-specific correlations with host metabolic and transcriptomic phenotypes. Fecal transplant experiments indicated that B6 microbes conferred resistance to fructose-induced weight gain in DBA mice (F = 43.1, P < 0.001), and Akkermansia colonization abrogated the fructose-induced weight gain (F = 17.8, P < 0.001) and glycemic dysfunctions (F = 11.8, P = 0.004) in DBA mice.

CONCLUSIONS

Our findings support that differential microbiota composition between mouse strains is partially responsible for host metabolic sensitivity to fructose, and that Akkermansia is a key bacterium that confers resistance to fructose-induced metabolic dysregulation.

Influence of 16S rRNA target region on the outcome of microbiome studies in soil and saliva samples

Next generation sequencing methods are widely used in evaluating the structure and functioning of microbial communities, especially those centered on 16S rRNA subunit. Since Illumina Miseq, the most used sequencing platform, does not allow the full sequencing of 16S rRNA gene, this study aims to evaluate whether the choice of different target regions might affect the outcome of microbiome studies regarding soil and saliva samples. V1V3, V3V4, V4V5 and V6V8 domains were studied, finding that while some regions showed differences in the detection of certain bacterial taxa and in the calculation of alpha diversity, especially in soil samples, the overall effect did not compromise the differentiation of any sample type in terms of taxonomic analysis at the genus level. 16S rRNA target regions did affect the detection of specific bacteria related to soil quality and development, and microbial genera used as health biomarkers in saliva. V1V3 region showed the closest similarity to internal sequencing control mock community B, suggesting it might be the most preferable choice regarding data reliability.

Metagenomic applications in exploration and development of novel enzymes from nature: a review

BACKGROUND

Microbial community has an essential role in various fields, especially the industrial sector. Microbes produce metabolites in the form of enzymes, which are one of the essential compounds for industrial processes. Unfortunately, there are still numerous microbes that cannot be identified and cultivated because of the limitations of the culture-based method. The metagenomic approach is a solution for researchers to overcome these problems. Metagenomics is a strategy used to analyze the genomes of microbial communities in the environment directly. Metagenomics application used to explore novel enzymes is essential because it allows researchers to obtain data on microbial diversity, reaching of 99% and various types of genes encoding an enzyme that has not yet been identified. Basic methods in metagenomics have been developed and are commonly used in various studies. A basic understanding of metagenomics for researchers is needed, especially young researchers to support the success of the research.

SHORT CONCLUSION

Therefore, this review was done in order to provide a deep understanding of metagenomics. It also discussed the application and basic methods of metagenomics in the exploration of novel enzymes, especially in the latest research. Several types of enzymes, such as cellulases, proteases, and lipases, which have been explored using metagenomics, were reviewed in this article.

Reservoir water stratification and mixing affects microbial community structure and functional community composition in a stratified drinking reservoir

To investigate how the aquatic bacterial community of a stratified reservoir drives the evolution of water parameters, the microbial community structure and network characteristics of bacteria in a stratified reservoir were investigated using Illumina MiSeq sequencing technology. A total of 42 phyla and 689 distinct genera were identified, which showed significant seasonal variation. Additionally, stratified variations in the bacterial community strongly reflected the vertical gradient and seasonal changes in water temperature, dissolved oxygen, and nutrition concentration. Furthermore, principal coordinate analysis indicated that most microorganisms were likely influenced by changes in water stratification conditions, exhibiting significant differences during the stratification period and mixing period based on Adonis, MRPP, and Anosim. Compared to the stratification period, 123 enhanced operational taxonomic units (OTUs; 29%) and 226 depleted OTUs (52%) were identified during the mixing period. Linear discriminant analysis effect size results showed that 15 major genera were enriched in the mixing period and 10 major genera were enriched in the stratification period. Importantly, network analysis revealed that the keystone species belonged to hgcI_clade, CL500-29, Acidibacter, Paucimonas, Flavobacterium, Prochlorothrix, Xanthomonadales, Chloroflexia, Burkholderiales, OPB56, KI89A_clade, Synechococcus, Caulobacter or were unclassified. Redundancy analysis showed that temperature, dissolved oxygen, pH, chlorophyll-α, total phosphorus, nitrate, and ammonia were important factors influencing the water bacterial community and function composition, which were consistent with the results of the Mantel test analysis. Furthermore, random forest analysis showed that temperature, dissolved oxygen, ammonia, and total dissolved phosphorous were the most important variables predicting water bacterial community and function community α- and β-diversity (P < 0.05). Overall, these results provide insight into the interactions between the microbial community and water quality evolution mechanism in Zhoucun reservoir.

The Microbiome in Immuno-oncology

The field of cancer therapy has been revolutionized through the use of immunotherapy, and treatment with these therapies now spans from early to late stage, and even into prevention. However, there are still a significant proportion of patients who do not derive long-term benefit from monotherapy and even combined therapy regimens, and novel approaches are needed to enhance therapeutic responses. Additionally, ideal biomarkers of response to immunotherapy are lacking and are critically needed. An emerging area of interest in immuno-oncology (IO) is the microbiome, which refers to the collection of microbes (and their genomes) that inhabit an individual and live in symbiosis. There is now evidence that these microbes (particularly those within the gut) impact host physiology and can impact responses to immunotherapy. The field of microbiome research in immuno-oncology is quickly emerging, with the potential use of the microbiome (in the gut as well as in the tumor) as a biomarker for response to IO as well as a therapeutic target. Notably, the microbiome may even have a role in toxicity to therapy. The state of the science in microbiome and IO are discussed and caveats and future directions are outlined to provide insights as we move forward as a field.

Construction of habitat-specific training sets to achieve species-level assignment in 16S rRNA gene datasets

BACKGROUND

The low cost of 16S rRNA gene sequencing facilitates population-scale molecular epidemiological studies. Existing computational algorithms can resolve 16S rRNA gene sequences into high-resolution amplicon sequence variants (ASVs), which represent consistent labels comparable across studies. Assigning these ASVs to species-level taxonomy strengthens the ecological and/or clinical relevance of 16S rRNA gene-based microbiota studies and further facilitates data comparison across studies.

RESULTS

To achieve this, we developed a broadly applicable method for constructing high-resolution training sets based on the phylogenic relationships among microbes found in a habitat of interest. When used with the naïve Bayesian Ribosomal Database Project (RDP) Classifier, this training set achieved species/supraspecies-level taxonomic assignment of 16S rRNA gene-derived ASVs. The key steps for generating such a training set are (1) constructing an accurate and comprehensive phylogenetic-based, habitat-specific database; (2) compiling multiple 16S rRNA gene sequences to represent the natural sequence variability of each taxon in the database; (3) trimming the training set to match the sequenced regions, if necessary; and (4) placing species sharing closely related sequences into a training-set-specific supraspecies taxonomic level to preserve subgenus-level resolution. As proof of principle, we developed a V1-V3 region training set for the bacterial microbiota of the human aerodigestive tract using the full-length 16S rRNA gene reference sequences compiled in our expanded Human Oral Microbiome Database (eHOMD). We also overcame technical limitations to successfully use Illumina sequences for the 16S rRNA gene V1-V3 region, the most informative segment for classifying bacteria native to the human aerodigestive tract. Finally, we generated a full-length eHOMD 16S rRNA gene training set, which we used in conjunction with an independent PacBio single molecule, real-time (SMRT)-sequenced sinonasal dataset to validate the representation of species in our training set. This also established the effectiveness of a full-length training set for assigning taxonomy of long-read 16S rRNA gene datasets.

CONCLUSION

Here, we present a systematic approach for constructing a phylogeny-based, high-resolution, habitat-specific training set that permits species/supraspecies-level taxonomic assignment to short- and long-read 16S rRNA gene-derived ASVs. This advancement enhances the ecological and/or clinical relevance of 16S rRNA gene-based microbiota studies. Video Abstract.

Spatial Modelling of Bacterial Diversity over the Selected Regions in Bangladesh by Next-Generation Sequencing: Role of Water Temperature

In this study, a spatial model has been developed to investigate the role of water temperature to the distribution of bacteria over the selected regions in the Bay of Bengal, located in the southern region of Bangladesh using next-generation sequencing. Bacterial concentration, quantitative polymerase chain reactions, and sequencing were performed on water samples and identified Acidobacteria, Actinobacteria, Bacteroidetes, Chlorobi, Chloroflexi, Cyanobacteria, Firmicutes, Nitrospirae, Planctomycetes, Proteobacteria, and Verrucomicrobia. The spatial model tessellated the parts of the Bay of Bengal with hexagons and analyzed the relationship between the distribution of bacteria and water temperature. A geographically weighted regression was used to observe whether water temperature contributed strongly or weakly to the distribution of bacteria. The residuals were examined to assess the model’s fitness. The spatial model has the potential to predict the bacterial diversity in the selected regions of Bangladesh.

Manipulating Gut Microbiota Composition to Enhance the Therapeutic Effect of Cancer Immunotherapy

In the past decade, a growing set of immunotherapies including immune checkpoint blockade, chimeric antigen receptor T cells, and bispecific antibodies propelled the advancement of oncology therapeutics. Accumulating evidence demonstrates that immunotherapy could eliminate tumors better than traditional chemotherapy or radiotherapy with lower risk of adverse events in numerous cancer types. Unfortunately, a substantial proportion of patients eventually acquire resistance to immunotherapy. By analyzing the differences between immunotherapy-sensitive and immunotherapy-resistant populations, it was noticed that the composition of gut microbiota is closely related to treatment effect. Moreover, in xenograft models, interventional regulation of gut microbiota could effectively enhance efficacy and relieve resistance during immunotherapy. Thus, we believe that gut microbiota composition might be helpful to explain the heterogeneity of treatment effect, and manipulating gut microbiota could be a promising adjuvant treatment for cancer immunotherapy. In this mini review, we focus on the latest understanding of the cross-talk between gut microbiota and host immunity. Moreover, we highlight the role of gut microbiota in cancer immunotherapy including immune checkpoint inhibitor and adoptive cell transfer.

Unravelling the effects of tropical land use conversion on the soil microbiome

BACKGROUND

The consequences of deforestation and agricultural treatments are complex and affect all trophic levels. Changes of microbial community structure and composition associated with rainforest conversion to managed systems such as rubber and oil palm plantations have been shown by 16S rRNA gene analysis previously, but functional profile shifts have been rarely addressed. In this study, we analysed the effects of rainforest conversion to different converted land use systems, including agroforestry ("jungle rubber") and monoculture plantations comprising rubber and oil palm, on soilborne microbial communities by metagenomic shotgun sequencing in Sumatra, Indonesia.

RESULTS

The diversity of bacteria and archaea decreased whereas diversity of fungi increased in the converted land use systems. The soil microbiome was dominated by bacteria followed by fungi. We detected negative effects of land use conversion on the abundance of Proteobacteria (especially on Rhizobiales and Burkholderiales) and positive effects on the abundance of Acidobacteria and Actinobacteria. These abundance changes were mainly driven by pH, C:N ratio, and Fe, C and N content. With increasing land use intensity, the functional diversity decreased for bacteria, archaea and fungi. Gene abundances of specific metabolisms such as nitrogen metabolism and carbon fixation were affected by land use management practices. The abundance of genes related to denitrification and nitrogen fixation increased in plantations while abundance of genes involved in nitrification and methane oxidation showed no significant difference. Linking taxonomic and functional assignment per read indicated that nitrogen metabolism-related genes were mostly assigned to members of the Rhizobiales and Burkholderiales. Abundances of carbon fixation genes increased also with increasing land use intensity. Motility- and interaction-related genes, especially genes involved in flagellar assembly and chemotaxis genes, decreased towards managed land use systems. This indicated a shift in mobility and interspecific interactions in bacterial communities within these soils.

CONCLUSIONS

Rainforest conversion to managed land use systems drastically affects structure and functional potential of soil microbial communities. The decrease in motility- and interaction-related functions from rainforest to converted land use systems indicated not only a shift in nutrient cycling but also in community dynamics. Fertilizer application and correspondingly higher availability of nutrients in intensively managed plantations lead to an environment in which interspecific interactions are not favoured compared to rainforest soils. We could directly link effects of land management, microbial community structure and functional potential for several metabolic processes. As our study is the first study of this size and detail on soil microbial communities in tropical systems, we provide a basis for further analyses.

Doing More with Less: A Comparison of 16S Hypervariable Regions in Search of Defining the Shrimp Microbiota

The shrimp has become the most valuable traded marine product in the world, and its microbiota plays an essential role in its development and overall health status. Massive high-throughput sequencing techniques using several hypervariable regions of the 16S rRNA gene are broadly applied in shrimp microbiota studies. However, it is essential to consider that the use of different hypervariable regions can influence the obtained data and the interpretation of the results. The present study compares the shrimp microbiota structure and composition obtained by three types of amplicons: one spanning both the V3 and V4 hypervariable regions (V3V4), one for the V3 region only (V3), and one for the V4 region only (V4) using the same experimental and bioinformatics protocols. Twenty-four samples from hepatopancreas and intestine were sequenced and evaluated using the GreenGenes and silva reference databases for clustering and taxonomic classification. In general, the V3V4 regions resulted in higher richness and diversity, followed by V3 and V4. All three regions establish an apparent clustering effect that discriminates between the two analyzed organs and describe a higher richness for the intestine and a higher diversity for the hepatopancreas samples. Proteobacteria was the most abundant phyla overall, and Cyanobacteria was more common in the intestine, whereas Firmicutes and Actinobacteria were more prevalent in hepatopancreas samples. Also, the genus Vibrio was significantly abundant in the intestine, as well as Acinetobacter and Pseudomonas in the hepatopancreas suggesting these taxa as markers for their respective organs independently of the sequenced region. The use of a single hypervariable region such as V3 may be a low-cost alternative that enables an adequate description of the shrimp microbiota, allowing for the development of strategies to continually monitor the microbial communities and detect changes that could indicate susceptibility to pathogens under real aquaculture conditions while the use of the full V3V4 regions can contribute to a more in-depth characterization of the microbial composition.

Simultaneous detection and comprehensive analysis of HPV and microbiome status of a cervical liquid-based cytology sample using Nanopore MinION sequencing

Human papillomavirus (HPV) is a major pathogen that causes cervical cancer and many other related diseases. HPV infection related cervical microbiome could be an induce factor of cervical cancer. However, it is uncommon to find a single test on the market that can simultaneously provide information on both HPV and the microbiome. Herein, a novel method was developed in this study to simultaneously detect HPV infection and microbiota composition promptly and accurately. It provides a new and simple way to detect vaginal pathogen situation and also provide valuable information for clinical diagnose. This approach combined multiplex PCR, which targeted both HPV16 E6E7 and full-length 16S rRNA, and Nanopore sequencing to generate enough information to understand the vagina condition of patients. One HPV positive liquid-based cytology (LBC) sample was sequenced and analyzed. After comparing with Illumina sequencing, the results from Nanopore showed a similar microbiome composition. An instant sequencing evaluation showed that 15 min sequencing is enough to identify the top 10 most abundant bacteria. Moreover, two HPV integration sites were identified and verified by Sanger sequencing. This approach has many potential applications in pathogen detection and can potentially aid in providing a more rapid clinical diagnosis.

Changes in the process performance and microbial community by addition of the metabolic uncoupler 3,3',4',5-tetrachlorosalicylanilide in sequencing batch reactors

A complete study about the effects of 3,3',4',5-tetrachlorosalicylanilide (TCS) on organic matter elimination performance, sludge production and on the microbial community of a biological wastewater treatment process has been performed. For this purpose two sequencing batch reactors (SBR) worked in parallel for 43 days with 0.8 mg·L^-1 of TCS (SBR-1) and without this metabolic uncoupler (SBR-2). Results indicated that 63.3% of sludge reduction was achieved in SBR-1. However, COD removal efficiency was maintained in similar values in both reactors (89.1% and 92.1% in SBR-1 and SBR-2, respectively). The exhaustive mixed liquor characterization led to know deeply the action mechanism of TCS. In this way, a 69% of adenosine triphosphate (ATP) reduction was observed in SBR-1 in comparison with values measured in SBR-2. On the contrary, an increase in soluble microbial products (SMP) and DNA concentrations occurred as a consequence of TCS addition. Thus, it could be concluded that sludge reduction due to TCS addition was due to both uncoupling effect and cellular lysis. Also, increase in all microbial hydrolytic enzymatic activities measured was observed, which explained the stable performance achieved in SBR-1 despite to the results explained above. It should be highlighted that this uncoupler should not be used in biological treatments that require nitrogen elimination because nitrifying bacteria were affected by its addition (Nitrosomonas and Nitrospira). Finally, the 16S rRNA gene amplicon sequencing informed that an important reduction of bacterial diversity resulted in SBR-1 due to TCS addition.

Diversity and geochemical community assembly processes of the living rare biosphere in a sand-and-gravel aquifer ecosystem in the Midwestern United States

Natural microbial communities consist of a limited number of abundant species and an extraordinarily diverse population of rare species referred to as the rare biosphere. Recent studies have revealed that the rare biosphere is not merely an inactive dormant population but may play substantial functional roles in the ecosystem. However, structure, activity and community assembly processes of the rare biosphere are poorly understood. In this study, we evaluated the present and living microbial community structures including rare populations in an aquifer ecosystem, the Mahomet Aquifer, USA, by both 16S rDNA and rRNA amplicon deep sequencing. The 13 groundwater samples formed three distinct groups based on the “entire” community structure, and the same grouping was obtained when focusing on the “rare” subcommunities (<0.1% of total abundance), while the “abundant” subcommunities (>1.0%) gave a different grouping. In the correlation analyses, the observed grouping pattern is associated with several geochemical factors, and structures of not only the entire community but also the rare subcommunity are correlated with geochemical profiles in the aquifer ecosystem. Our findings first indicate that the living rare biosphere in the aquifer system has the metabolic potential to adapt to local geochemical factors which dictate the community assembly processes.

Comparative evaluation of three archaeal primer pairs for exploring archaeal communities in deep-sea sediments and permafrost soils

16S rRNA gene profiling is a powerful method for characterizing microbial communities; however, no universal primer pair can target all bacteria and archaea, resulting in different primer pairs which may impact the diversity profile obtained. Here, we evaluated three pairs of high-throughput sequencing primers for characterizing archaeal communities from deep-sea sediments and permafrost soils. The results show that primer pair Arch519/Arch915 (V4-V5 regions) produced the highest alpha diversity estimates, followed by Arch349f/Arch806r (V3-V4 regions) and A751f/AU1204r (V5-V7 regions) in both sample types. The archaeal taxonomic compositions and the relative abundance estimates of archaeal communities are influenced by the primer pairs. Beta diversity of the archaeal community detected by the three primer pairs reveals that primer pairs Arch349f/Arch806r and Arch519f/Arch915r are biased toward detection of Halobacteriales, Methanobacteriales and MBG-E/Hydrothermarchaeota, whereas the primer pairs Arch519f/Arch915r and A751f/UA1204r are biased to detect MBG-B/Lokiarchaeota, and the primers pairs Arch349f/Arch806r and A751f/UA1204r are biased to detect Methanomicrobiales and Methanosarcinales. The data suggest that the alpha and beta diversities of archaeal communities as well as the community compositions are influenced by the primer pair choice. This finding provides researchers with valuable experimental insight for selection of appropriate archaeal primer pairs to characterize archaeal communities.

Linking heterotrophic bacterioplankton community composition to the optical dynamics of dissolved organic matter in a large eutrophic Chinese lake

Elucidation of the linkages between the bacterial community composition and chromophoric dissolved organic matter (CDOM) in lake ecosystems is critical for the understanding of the inland water carbon cycling. Despite substantial research into the relationship between the bacteria community and the bulk DOM pool, knowledge of the specific relationship between the optical dynamics of DOM and the bacterioplankton community in lake ecosystems is still poor. We investigated the linkages between the optical dynamics of DOM and bacteria composition in shallow eutrophic Lake Taihu, China. Redundancy Analysis (RDA) indicated that besides water temperature and phytoplankton biomass, also CDOM was an important factor determining the composition of the bacterial community. Generalized Additive Models (GAM) showed that terrestrial humic-like C1 and tyrosine-like C4 were the key factors explaining the abundance of the main bacterial clades. C1 was closely correlated with Verrucomicrobia, Actinobacteria, Alphaproteobacteria, Betaproteobacteria and Planctomycetes, and C4 was closely related to the latter two and to Bacteroidetes. At family level, the dominant families - Pelagibacteraceae (Alphaproteobacteria) and Gemmataceae (Planctomycetes) - were related to both allochthonous and autochthonous CDOM fluorophores but responded differently to the various CDOM components. Tryptophan-like C2 was significantly and positively correlated with Gemmataceae and Ellin6075 (Acidobacteria). Additionally, we found that the biomasses of Cyanophyta, terrestrial humic-like C1, tryptophan-like C4 and C5 were significantly related to the richness of heterotrophic bacterioplankton. Our results provide new insight into the relationship between bacteria and DOM optical dynamics although the mechanisms leading to these relationships need further experimental investigations.

Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.

Can Targeting Non-Contiguous V-Regions With Paired-End Sequencing Improve 16S rRNA-Based Taxonomic Resolution of Microbiomes?: An In Silico Evaluation

Background: Next-generation sequencing (NGS) technologies have enabled probing of microbial diversity in different environmental niches with unprecedented sequencing depth. However, due to read-length limitations of popular NGS technologies, 16S amplicon sequencing-based microbiome studies rely on targeting short stretches of the 16S rRNA gene encompassing a selection of variable (V) regions. In most cases, such a short stretch constitutes a single V-region or a couple of V-regions placed adjacent to each other on the 16S rRNA gene. Given that different V-regions have different resolving ability with respect to various taxonomic groups, selecting the optimal V-region (or a combination thereof) remains a challenge.

Methods: The accuracy of taxonomic profiles generated from sequences encompassing 1) individual V-regions, 2) adjacent V-regions, and 3) pairs of non-contiguous V-regions were assessed and compared. Subsequently, the discriminating capability of different V-regions with respect to different taxonomic lineages was assessed. The possibility of using paired-end sequencing protocols to target combinations of non-adjacent V-regions was finally evaluated with respect to the utility of such an experimental design in providing improved taxonomic resolution.

Results: Extensive validation with simulated microbiome datasets mimicking different environmental and host-associated microbiome samples suggest that targeting certain combinations of non-contiguously placed V-regions might yield better taxonomic classification accuracy compared to conventional 16S amplicon sequencing targets. This work also puts forward a novel in silico combinatorial strategy that enables creation of consensus taxonomic profiles from experiments targeting multiple pair-wise combinations of V-regions to improve accuracy in taxonomic classification.

Conclusion: The study suggests that targeting non-contiguous V-regions with paired-end sequencing can improve 16S rRNA–based taxonomic resolution of microbiomes. Furthermore, employing the novel in silico combinatorial strategy can improve taxonomic classification without any significant additional experimental costs and/or efforts. The empirical observations obtained can potentially serve as a guideline for future 16S microbiome studies, and facilitate researchers in choosing the optimal combination of V-regions for a specific experiment/sampled environment.

The Impact of Intratumoral and Gastrointestinal Microbiota on Systemic Cancer Therapy

The human microbiome is a complex aggregate of microorganisms, and their genomes exert a number of influences crucial to the metabolic, immunologic, hormonal, and homeostatic function of the host. Recent work, both in preclinical mouse models and human studies, has shed light on the impact of gut and tumor microbiota on responses to systemic anticancer therapeutics. In light of this, strategies to target the microbiome to improve therapeutic responses are underway, including efforts to target gut and intratumoral microbes. Here, we discuss mechanisms by which microbiota may impact systemic and antitumor immunity, in addition to outstanding questions in the field. A deeper understanding of these is critical as we devise putative strategies to target the microbiome.

Switching on the light: using metagenomic shotgun sequencing to characterize the intestinal microbiome of Atlantic cod

Atlantic cod (Gadus morhua) is an ecologically important species with a wide-spread distribution in the North Atlantic Ocean, yet little is known about the diversity of its intestinal microbiome in its natural habitat. No geographical differentiation in this microbiome was observed based on 16S rRNA amplicon analyses, yet such finding may result from an inherent lack of power of this method to resolve fine-scaled biological complexity. Here, we use metagenomic shotgun sequencing to investigate the intestinal microbiome of 19 adult Atlantic cod individuals from two coastal populations in Norway-located 470 km apart. Resolving the species community to unprecedented resolution, we identify two abundant species, Photobacterium iliopiscarium and Photobacterium kishitanii, which comprise over 50% of the classified reads. Interestingly, the intestinal P. kishitanii strains have functionally intact lux genes, and its high abundance suggests that fish intestines form an important part of its ecological niche. These observations support a hypothesis that bioluminescence plays an ecological role in the marine food web. Despite our improved taxonomical resolution, we identify no geographical differences in bacterial community structure, indicating that the intestinal microbiome of these coastal cod is colonized by a limited number of closely related bacterial species with a broad geographical distribution.

Long-Term Temperature Stress in the Coral Model Aiptasia Supports the "Anna Karenina Principle" for Bacterial Microbiomes

The understanding of host-microbial partnerships has become a hot topic during the last decade as it has been shown that associated microbiota play critical roles in the host physiological functions and susceptibility to diseases. Moreover, the microbiome may contribute to host resilience to environmental stressors. The sea anemone Aiptasia is a good laboratory model system to study corals and their microbial symbiosis. In this regard, studying its bacterial microbiota provides a better understanding of cnidarian metaorganisms as a whole. Here, we investigated the bacterial communities of different Aiptasia host-symbiont combinations under long-term heat stress in laboratory conditions. Following a 16S rRNA gene sequencing approach we were able to detect significant differences in the bacterial composition and structure of Aiptasia reared at different temperatures. A higher number of taxa (i.e., species richness), and consequently increased α-diversity and β-dispersion, were observed in the microbiomes of heat-stressed individuals across all host strains and experimental batches. Our findings are in line with the recently proposed Anna Karenina principle (AKP) for animal microbiomes, which states that dysbiotic or stressed organisms have a more variable and unstable microbiome than healthy ones. Microbial interactions affect the fitness and survival of their hosts, thus exploring the AKP effect on animal microbiomes is important to understand host resilience. Our data contributes to the current knowledge of the Aiptasia holobiont and to the growing field of study of host-associated microbiomes.

Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis

Bovine mastitis continues to be a complex disease associated with significant economic loss in dairy industries worldwide. The incidence rate of subclinical mastitis (IRSCM) can show substantial variation among different farms; however, the milk microbiota, which have a direct influence on bovine mammary gland health, have never been associated with the IRSCM. Here, we aimed to use high-throughput DNA sequencing to describe the milk microbiota from two dairy farms with different IRSCMs and to identify the predominant mastitis pathogens along with commensal or potential beneficial bacteria. Our study showed that Klebsiella, Escherichia-Shigella, and Streptococcus were the mastitis-causing pathogens in farm A (with a lower IRSCM), while Streptococcus and Corynebacterium were the mastitis-causing pathogens in farm B (with a higher IRSCM). The relative abundance of all pathogens in farm B (22.12%) was higher than that in farm A (9.82%). However, the genus Bacillus was more prevalent in farm A. These results may be helpful for explaining the lower IRSCM in farm A. Additionally, the gut-associated genera Prevotella, Ruminococcus, Bacteroides, Rikenella, and Alistipes were prevalent in all milk samples, suggesting gut bacteria can be one of the predominant microbial contamination in milk. Moreover, Listeria monocytogenes (a foodborne pathogen) was found to be prevalent in farm A, even though it had a lower IRSCM. Overall, our study showed complex diversity between the milk microbiota in dairy farms with different IRSCMs. This suggests that variation in IRSCMs may not only be determined by the heterogeneity and prevalence of mastitis-causing pathogens but also be associated with potential beneficial bacteria. In the future, milk microbiota should be considered in bovine mammary gland health management. This would be helpful for both the establishment of a targeted mastitis control system and the control of the safety and quality of dairy products.

A Single Vibrionales 16S rRNA Oligotype Dominates the Intestinal Microbiome in Two Geographically Separated Atlantic cod Populations

Atlantic cod (Gadus morhua) provides an interesting species for the study of host-microbe interactions because it lacks the MHC II complex that is involved in the presentation of extracellular pathogens. Nonetheless, little is known about the diversity of its microbiome in natural populations. Here, we use high-throughput sequencing of the 16S rRNA V4 region, amplified with the primer design of the Earth Microbiome Project (EMP), to investigate the microbial composition in gut content and mucosa of 22 adult individuals from two coastal populations in Norway, located 470 km apart. We identify a core microbiome of 23 OTUs (97% sequence similarity) in all individuals that comprises 93% of the total number of reads. The most abundant orders are classified as Vibrionales, Fusobacteriales, Clostridiales, and Bacteroidales. While mucosal samples show significantly lower diversity than gut content samples, no differences in OTU community composition are observed between the two geographically separated populations. All specimens share a limited number of abundant OTUs. Moreover, the most abundant OTU consists of a single oligotype (order Vibrionales, genus Photobacterium) that represents nearly 50% of the reads in both locations. Our results suggest that these microbiomes comprise a limited number of species or that the EMP V4 primers do not yield sufficient resolution to confidently separate these communities. Our study contributes to a growing body of literature that shows limited spatial differentiation of the intestinal microbiomes in marine fish based on 16S rRNA sequencing, highlighting the need for multi-gene approaches to provide more insight into the diversity of these communities.