Quantifying microbial guilds.

The ecological role of microorganisms is of utmost importance due to their multiple interactions with the environment. However, assessing the contribution of individual taxonomic groups has proven difficult despite the availability of high throughput data, hindering our understanding of such complex systems. Here, we propose a quantitative definition of guild that is readily applicable to metagenomic data. Our framework focuses on the functional character of protein sequences, as well as their diversifying nature. First, we discriminate functional sequences from the whole sequence space corresponding to a gene annotation to then quantify their contribution to the guild composition across environments. In addition, we identify and distinguish functional implementations, which are sequence spaces that have different ways of carrying out the function. In contrast, we found that orthology delineation did not consistently align with ecologically (or functionally) distinct implementations of the function. We demonstrate the value of our approach with two case studies: the ammonia oxidation and polyamine uptake guilds from the Malaspina circumnavigation cruise, revealing novel ecological dynamics of the latter in marine ecosystems. Thus, the quantification of guilds helps us to assess the functional role of different taxonomic groups with profound implications on the study of microbial communities.

In situ metagenomics: A platform for rapid sequencing and analysis of metagenomes in less than one day.

We present here a complete system for metagenomic analysis that allows performing the sequencing and analysis of a medium-size metagenome in less than one day. This unprecedented development was possible due to the conjunction of state-of-the-art experimental and computational advances: a portable laboratory suitable for DNA extraction and sequencing with nanopore technology; the powerful metagenomic analysis pipeline SqueezeMeta, capable to provide a complete analysis in a few hours and using scarce computational resources; and tools for the automatic inspection of the results via a graphical user interface, that can be coupled to a web server to allow remote visualization of data (SQMtools and SQMxplore). We have tested the feasibility of our approach in the sequencing of the microbiota associated to volcanic rocks in La Palma, Canary Islands. Also, we did a two-day sampling campaign of marine waters in which the results obtained on the first day guided the experimental design of the second day. We demonstrate that it is possible to generate metagenomic information in less than one day, making it feasible to obtain taxonomic and functional profiles fast and efficiently, even in field conditions. This capacity can be used in the further to perform real-time functional and taxonomic monitoring of microbial communities in remote areas.

In silico evaluation and selection of the best 16S rRNA gene primers for use in next-generation sequencing to detect oral bacteria and archaea.

BACKGROUND: Sequencing has been widely used to study the composition of the oral microbiome present in various health conditions. The extent of the coverage of the 16S rRNA gene primers employed for this purpose has not, however, been evaluated in silico using oral-specific databases. This paper analyses these primers using two databases containing 16S rRNA sequences from bacteria and archaea found in the human mouth and describes some of the best primers for each domain. RESULTS: A total of 369 distinct individual primers were identified from sequencing studies of the oral microbiome and other ecosystems. These were evaluated against a database reported in the literature of 16S rRNA sequences obtained from oral bacteria, which was modified by our group, and a self-created oral archaea database. Both databases contained the genomic variants detected for each included species. Primers were evaluated at the variant and species levels, and those with a species coverage (SC) ≥75.00% were selected for the pair analyses. All possible combinations of the forward and reverse primers were identified, with the resulting 4638 primer pairs also evaluated using the two databases. The best bacteria-specific pairs targeted the 3-4, 4-7, and 3-7 16S rRNA gene regions, with SC levels of 98.83-97.14%; meanwhile, the optimum archaea-specific primer pairs amplified regions 5-6, 3-6, and 3-6, with SC estimates of 95.88%. Finally, the best pairs for detecting both domains targeted regions 4-5, 3-5, and 5-9, and produced SC values of 95.71-94.54% and 99.48-96.91% for bacteria and archaea, respectively. CONCLUSIONS: Given the three amplicon length categories (100-300, 301-600, and >600 base pairs), the primer pairs with the best coverage values for detecting oral bacteria were as follows: KP_F048-OP_R043 (region 3-4; primer pair position for Escherichia coli J01859.1: 342-529), KP_F051-OP_R030 (4-7; 514-1079), and KP_F048-OP_R030 (3-7; 342-1079). For detecting oral archaea, these were as follows: OP_F066-KP_R013 (5-6; 784-undefined), KP_F020-KP_R013 (3-6; 518-undefined), and OP_F114-KP_R013 (3-6; 340-undefined). Lastly, for detecting both domains jointly they were KP_F020-KP_R032 (4-5; 518-801), OP_F114-KP_R031 (3-5; 340-801), and OP_F066-OP_R121 (5-9; 784-1405). The primer pairs with the best coverage identified herein are not among those described most widely in the oral microbiome literature. Video Abstract.

M&Ms: a versatile software for building microbial mock communities.

SUMMARY: Advances in sequencing technologies have triggered the development of many bioinformatic tools aimed to analyze 16S rDNA sequencing data. As these tools need to be tested, it is important to simulate datasets that resemble samples from different environments. Here, we introduce M&Ms, a user-friendly open-source bioinformatic tool to produce different 16S rDNA datasets from reference sequences, based on pragmatic ecological parameters. It creates sequence libraries for 'in silico' microbial communities with user-controlled richness, evenness, microdiversity and source environment. M&Ms allows the user to generate simple to complex read datasets based on real parameters that can be used in developing bioinformatic software or in benchmarking current tools. AVAILABILITY AND IMPLEMENTATION: The source code of M&Ms is freely available at https://github.com/ggnatalia/MMs (GPL-3.0 License). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fungal and ciliate protozoa are the main rumen microbes associated with methane emissions in dairy cattle.

BACKGROUND: Mitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions. RESULTS: The ß-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals. CONCLUSIONS: Methane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.

Metagenomic and metabolic analyses of poly-extreme microbiome from an active crater volcano lake.

El Chichón volcano is one of the most active volcanoes in Mexico. Previous studies have described its poly-extreme conditions and its bacterial composition, although the functional features of the complete microbiome have not been characterized yet. By using metabarcoding analysis, metagenomics, metabolomics and enzymology techniques, the microbiome of the crater lake was characterized in this study. New information is provided on the taxonomic and functional diversity of the representative Archaea phyla, Crenarchaeota and Euryarchaeota, as well as those that are representative of Bacteria, Thermotogales and Aquificae. With culture of microbial consortia and with the genetic information collected from the natural environment sampling, metabolic interactions were identified between prokaryotes, which can withstand multiple extreme conditions. The existence of a close relationship between the biogeochemical cycles of carbon and sulfur in an active volcano has been proposed, while the relationship in the energy metabolism of thermoacidophilic bacteria and archaea in this multi-extreme environment was biochemically revealed for the first time. These findings contribute towards understanding microbial metabolism under extreme conditions, and provide potential knowledge pertaining to "microbial dark matter", which can be applied to biotechnological processes and evolutionary studies.

A dimensional reduction approach to modulate the core ruminal microbiome associated with methane emissions via selective breeding.

The rumen is a complex microbial system of substantial importance in terms of greenhouse gas emissions and feed efficiency. This study proposes combining metagenomic and host genomic data for selective breeding of the cow hologenome toward reduced methane emissions. We analyzed nanopore long reads from the rumen metagenome of 437 Holstein cows from 14 commercial herds in 4 northern regions in Spain. After filtering, data were treated as compositional. The large complexity of the rumen microbiota was aggregated, through principal component analysis (PCA), into few principal components (PC) that were used as proxies of the core metagenome. The PCA allowed us to condense the huge and fuzzy taxonomical and functional information from the metagenome into a few PC. Bivariate animal models were applied using these PC and methane production as phenotypes. The variability condensed in these PC is controlled by the cow genome, with heritability estimates for the first PC of ~0.30 at all taxonomic levels, with a large probability (>83%) of the posterior distribution being >0.20 and with the 95% highest posterior density interval (95%HPD) not containing zero. Most genetic correlation estimates between PC1 and methane were large (≥0.70), with most of the posterior distribution (>82%) being >0.50 and with its 95%HPD not containing zero. Enteric methane production was positively associated with relative abundance of eukaryotes (protozoa and fungi) through the first component of the PCA at phylum, class, order, family, and genus. Nanopore long reads allowed the characterization of the core rumen metagenome using whole-metagenome sequencing, and the purposed aggregated variables could be used in animal breeding programs to reduce methane emissions in future generations.

SQMtools: automated processing and visual analysis of 'omics data with R and anvi'o.

BACKGROUND: The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches. RESULTS: Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment. CONCLUSIONS: Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.

Metagenomic analysis of an urban resistome before and after wastewater treatment.

Determining the effect of wastewater treatment in water resistome is a topic of interest for water quality, mainly under re-use and One-Health perspectives. The resistome, the plasmidome, and the bacterial community composition of samples from influents and treated effluents from a wastewater treatment plant located in Northern Portugal were studied using metagenomic techniques. Wastewater treatment contributed to reduce the abundance of resistance genes and of plasmid replicons, coinciding with a decline in the number of intrinsic resistance genes from Enterobacteriaceae, as well as with a reduction in the relative abundance of Firmicutes and Proteobacteria after treatment. These taxons comprise bacterial pathogens, including those belonging to the ESKAPE group, which encompasses bacteria with the highest risk of acquiring antibiotic resistance, being the most relevant hosts of resistance genes acquired through horizontal gene transfer. Our results support that wastewater treatment efficiently removes the hosts of antibiotic resistance genes and, consequently, the harboured antibiotic resistance genes. Principal component analysis indicates that the resistome and the bacterial composition clustered together in influent samples, while did not cluster in final effluent samples. Our results suggest that wastewater treatment mitigates the environmental dissemination of urban resistome, through the removal of the hosts harbouring mobile resistance genes.

Microbiota characterization of sheep milk and its association with somatic cell count using 16s rRNA gene sequencing.

This work aimed to use 16S ribosomal RNA sequencing with the Illumina MiSeq platform to describe the milk microbiota from 50 healthy Assaf ewes. The global observed microbial community for clinically healthy milk samples analysed was complex and showed a vast diversity. The core microbiota of the sheep milk includes five genera: Staphylococcus, Lactobacillus, Corynebacterium, Streptococcus and Escherichia/Shigella. Although there are some differences, some of these genera are common with the microbiota core pattern of milk from other species, especially with dairy cows. The microbial composition of the studied samples, based on the definition of amplicon sequence variants, was analysed through a correlation network. A preliminary analysis by grouping the milk samples based on their somatic cell count (SCC), which is considered an indicator of subclinical mastitis (SM), showed certain differences for the core of the samples identified as SM. The differences in the microbiota diversity pattern among samples might also suggest that subclinical mastitis would be associated with the significant increase in some genera that are inhabitants of the mammary gland and a remarkable concomitant reduction in the microbial diversity. Additionally, we have also presented here a preliminary analysis to assess the impact of the sheep milk microbiome on SCC, as an indicator of subclinical mastitis. The results here reported provide a first characterization of the sheep milk microbiota and settle the basis for future studies in this field.

Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes.

BACKGROUND: Metagenomes can be analysed using different approaches and tools. One of the most important distinctions is the way to perform taxonomic and functional assignment, choosing between the use of assembly algorithms or the direct analysis of raw sequence reads instead by homology searching, k-mer analysys, or detection of marker genes. Many instances of each approach can be found in the literature, but to the best of our knowledge no evaluation of their different performances has been carried on, and we question if their results are comparable. RESULTS: We have analysed several real and mock metagenomes using different methodologies and tools, and compared the resulting taxonomic and functional profiles. Our results show that database completeness (the representation of diverse organisms and taxa in it) is the main factor determining the performance of the methods relying on direct read assignment either by homology, k-mer composition or similarity to marker genes, while methods relying on assembly and assignment of predicted genes are most influenced by metagenomic size, that in turn determines the completeness of the assembly (the percentage of read that were assembled). CONCLUSIONS: Although differences exist, taxonomic profiles are rather similar between raw read assignment and assembly assignment methods, while they are more divergent for methods based on k-mers and marker genes. Regarding functional annotation, analysis of raw reads retrieves more functions, but it also makes a substantial number of over-predictions. Assembly methods are more advantageous as the size of the metagenome grows bigger.

Microdiversity ensures the maintenance of functional microbial communities under changing environmental conditions.

Microdiversity can lead to different ecotypes within the same species. These are assumed to provide stability in time and space to those species. However, the role of microdiversity in the stability of whole microbial communities remains underexplored. Understanding the drivers of microbial community stability is necessary to predict community response to future disturbances. Here, we analyzed 16S rRNA gene amplicons from eight different temperate bog lakes at the 97% OTU and amplicon sequence variant (ASV) levels and found ecotypes within the same OTU with different distribution patterns in space and time. We observed that these ecotypes are adapted to different values of environmental factors such as water temperature and oxygen concentration. Our results showed that the existence of several ASVs within a OTU favored its persistence across changing environmental conditions. We propose that microdiversity aids the stability of microbial communities in the face of fluctuations in environmental factors.

Mycobiome Profiles in Breast Milk from Healthy Women Depend on Mode of Delivery, Geographic Location, and Interaction with Bacteria.

Recent studies report the presence of fungal species in breast milk of healthy mothers, suggesting a potential role in infant mycobiome development. In the present work, we aimed to determine whether the healthy human breast milk mycobiota is influenced by geographical location and mode of delivery, as well as to investigate its interaction with bacterial profiles in the same samples. A total of 80 mature breast milk samples from 4 different countries were analyzed by Illumina sequencing of the internal transcribed spacer 1 (ITS1) region, joining the 18S and 5.8S regions of the fungal rRNA region. Basidiomycota and Ascomycota were found to be the dominant phyla, with Malassezia and Davidiella being the most prevalent genera across countries. A core formed by Malassezia, Davidiella, Sistotrema, and Penicillium was shared in the milk samples from the different origins, although specific shifts in mycobiome composition were associated with geographic location and delivery mode. The presence of fungi in the breast milk samples was further confirmed by culture and isolate characterization, and fungal loads were estimated by quantitative PCR (qPCR) targeting the fungal ITS1 region. Cooccurrence network analysis of bacteria and fungi showed complex interactions that were influenced by geographical location, mode of delivery, maternal age, and pregestational body mass index. The presence of a breast milk mycobiome was confirmed in all samples analyzed, regardless of the geographic origin.IMPORTANCE During recent years, human breast milk has been documented as a potential source of bacteria for the newborn. Recently, we have reported the presence of fungi in breast milk from healthy mothers. It is well known that environmental and perinatal factors can affect milk bacteria; however, the impact on milk fungi is still unknown. The current report describes fungal communities (mycobiota) in breast milk samples across different geographic locations and the influence of the mode of delivery. We also provide novel insights on bacterium-fungus interactions, taking into account environmental and perinatal factors. We identified a core of four genera shared across locations, consisting of Malassezia, Davidiella, Sistotrema, and Penicillium, which have been reported to be present in the infant gut. Our data confirm the presence of fungi in breast milk across continents and support the potential role of breast milk in the initial seeding of fungal species in the infant gut.

Draft genome sequences of Cylindrospermopsis raciborskii strains CS-508 and MVCC14, isolated from freshwater bloom events in Australia and Uruguay.

Members of the genus Cylindrospermopsis represent an important environmental and health concern. Strains CS-508 and MVCC14 of C. raciborskii were isolated from freshwater reservoirs located in Australia and Uruguay, respectively. While CS-508 has been reported as non-toxic, MVCC14 is a saxitoxin (STX) producer. We annotated the draft genomes of these C. raciborskii strains using the assembly of reads obtained from Illumina MiSeq sequencing. The final assemblies resulted in genome sizes close to 3.6 Mbp for both strains and included 3202 ORFs for CS-508 (in 163 contigs) and 3560 ORFs for MVCC14 (in 99 contigs). Finally, both the average nucleotide identity (ANI) and the similarity of gene content indicate that these two genomes should be considered as strains of the C. raciborskii species.

Diurnal Changes in Active Carbon and Nitrogen Pathways Along the Temperature Gradient in Porcelana Hot Spring Microbial Mat.

Composition, carbon and nitrogen uptake, and gene transcription of microbial mat communities in Porcelana neutral hot spring (Northern Chilean Patagonia) were analyzed using metagenomics, metatranscriptomics and isotopically labeled carbon (H13CO3) and nitrogen (15NH4Cl and K15NO3) assimilation rates. The microbial mat community included 31 phyla, of which only Cyanobacteria and Chloroflexi were dominant. At 58°C both phyla co-occurred, with similar contributions in relative abundances in metagenomes and total transcriptional activity. At 66°C, filamentous anoxygenic phototrophic Chloroflexi were >90% responsible for the total transcriptional activity recovered, while Cyanobacteria contributed most metagenomics and metatranscriptomics reads at 48°C. According to such reads, phototrophy was carried out both through oxygenic photosynthesis by Cyanobacteria (mostly Mastigocladus) and anoxygenic phototrophy due mainly to Chloroflexi. Inorganic carbon assimilation through the Calvin-Benson cycle was almost exclusively due to Mastigocladus, which was the main primary producer at lower temperatures. Two other CO2 fixation pathways were active at certain times and temperatures as indicated by transcripts: 3-hydroxypropionate (3-HP) bi-cycle due to Chloroflexi and 3-hydroxypropionate-4-hydroxybutyrate (HH) cycle carried out by Thaumarchaeota. The active transcription of the genes involved in these C-fixation pathways correlated with high in situ determined carbon fixation rates. In situ measurements of ammonia assimilation and nitrogen fixation (exclusively attributed to Cyanobacteria and mostly to Mastigocladus sp.) showed these were the most important nitrogen acquisition pathways at 58 and 48°C. At 66°C ammonia oxidation genes were actively transcribed (mostly due to Thaumarchaeota). Reads indicated that denitrification was present as a nitrogen sink at all temperatures and that dissimilatory nitrate reduction to ammonia (DNRA) contributed very little. The combination of metagenomic and metatranscriptomic analysis with in situ assimilation rates, allowed the reconstruction of day and night carbon and nitrogen assimilation pathways together with the contribution of keystone microorganisms in this natural hot spring microbial mat.

Bacterial lineages putatively associated with the dissemination of antibiotic resistance genes in a full-scale urban wastewater treatment plant.

Urban wastewater treatment plants (UWTPs) are reservoirs of antibiotic resistance. Wastewater treatment changes the bacterial community and inevitably impacts the fate of antibiotic resistant bacteria and antibiotic resistance genes (ARGs). Some bacterial groups are major carriers of ARGs and hence, their elimination during wastewater treatment may contribute to increasing resistance removal efficiency. This study, conducted at a full-scale UWTP, evaluated variations in the bacterial community and ARGs loads and explored possible associations among them. With that aim, the bacterial community composition (16S rRNA gene Illumina sequencing) and ARGs abundance (real-time PCR) were characterized in samples of raw wastewater (RWW), secondary effluent (sTWW), after UV disinfection (tTWW), and after a period of 3 days storage to monitoring possible bacterial regrowth (tTWW-RE). Culturable enterobacteria were also enumerated. Secondary treatment was associated with the most dramatic bacterial community variations and coincided with reductions of ~2 log-units in the ARGs abundance. In contrast, no significant changes in the bacterial community composition and ARGs abundance were observed after UV disinfection of sTWW. Nevertheless, after UV treatment, viability losses were indicated ~2 log-units reductions of culturable enterobacteria. The analysed ARGs (qnrS, blaCTX-M, blaOXA-A, blaTEM, blaSHV, sul1, sul2, and intI1) were strongly correlated with taxa more abundant in RWW than in the other types of water, and which associated with humans and animals, such as members of the families Campylobacteraceae, Comamonadaceae, Aeromonadaceae, Moraxellaceae, and Bacteroidaceae. Further knowledge of the dynamics of the bacterial community during wastewater treatment and its relationship with ARGs variations may contribute with information useful for wastewater treatment optimization, aiming at a more effective resistance control.

Draft Genome Sequence of the Extremely Desiccation-Tolerant Cyanobacterium Gloeocapsopsis sp. Strain AAB1.

Gloeocapsopsis sp. strain AAB1 is an extremely desiccation-tolerant cyanobacterium isolated from translucent quartz stones from the Atacama Desert (Chile). Here, we report its draft genome sequence, which consists of 137 contigs with an ∼5.4-Mb genome size. The annotation revealed 5,641 coding DNA sequences, 38 tRNA genes, and 5 rRNA genes.

SqueezeMeta, A Highly Portable, Fully Automatic Metagenomic Analysis Pipeline.

The improvement of sequencing technologies has facilitated generalization of metagenomic sequencing, which has become a standard procedure for analyzing the structure and functionality of microbiomes. Bioinformatic analysis of sequencing results poses a challenge because it involves many different complex steps. SqueezeMeta is a fully automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support that enables co-assembly of related metagenomes and retrieval of individual genomes via binning procedures. SqueezeMeta features several unique characteristics: co-assembly procedure or co-assembly of unlimited number of metagenomes via merging of individual assembled metagenomes, both with read mapping for estimation of the abundances of genes in each metagenome. It also includes binning and bin checking for retrieving individual genomes. Internal checks for the assembly and binning steps provide information about the consistency of contigs and bins. Moreover, results are stored in a MySQL database, where they can be easily exported and shared, and can be inspected anywhere using a flexible web interface that allows simple creation of complex queries. We illustrate the potential of SqueezeMeta by analyzing 32 gut metagenomes in a fully automatic way, enabling retrieval of several million genes and several hundreds of genomic bins. One of the motivations in the development of SqueezeMeta was producing a software capable of running in small desktop computers and thus amenable to all users and settings. We were also able to co-assemble two of these metagenomes and complete the full analysis in less than one day using a simple laptop computer. This reveals the capacity of SqueezeMeta to run without high-performance computing infrastructure and in absence of any network connectivity. It is therefore adequate for in situ, real time analysis of metagenomes produced by nanopore sequencing. SqueezeMeta can be downloaded from https://github.com/jtamames/SqueezeMeta.

Antibiotic Resistance Gene Detection in the Microbiome Context.

Within the past decade, microbiologists have moved from detecting single antibiotic resistance genes (ARGs) to detecting all known resistance genes within a sample due to advances in next generation sequencing. This has provided a wealth of data on the variation and relative abundances of ARGs present in a total bacterial population. However, to use these data in terms of therapy or risk to patients, they must be analyzed in the context of the background microbiome. Using a quantitative PCR ARG chip and 16S rRNA amplicon sequencing, we have sought to identify the ARGs and bacteria present in a fecal sample of a healthy adult using genomic tools. Of the 42 ARGs detected, 12 fitted into the ResCon1 category of ARGs: cfxA, cphA, bacA, sul3, aadE, blaTEM, aphA1, aphA3, aph(2')-Id, aacA/aphd, catA1, and vanC. Therefore, we describe these 12 genes as the core resistome of this person's fecal microbiome and the remaining 30 ARGs as descriptors of the microbial population within the fecal microbiome. The dominant phyla and genera agree with those previously detected in the greatest abundances in fecal samples of healthy humans. The majority of the ARGs detected were associated with the presence of specific bacterial taxa, which were confirmed using microbiome analysis. We acknowledge the limitations of the data in the context of the limited sample set. However, the principle of combining qPCR and microbiome analysis was shown to be helpful to identify the association of the ARGs with specific taxa.

Relating genomic characteristics to environmental preferences and ubiquity in different microbial taxa.

BACKGROUND: Despite the important role that microorganisms play in environmental processes, the low percentage of cultured microbes (5%) has limited, until now, our knowledge of their ecological strategies. However, the development of high-throughput sequencing has generated a huge amount of genomic and metagenomic data without the need of culturing that can be used to study ecological questions. This study aims to estimate the functional capabilities, genomic sizes and 16S copy number of different taxa in relation to their ubiquity and their environmental preferences. RESULTS: To achieve this goal, we compiled data regarding the presence of each prokaryotic genera in diverse environments. Then, genomic characteristics such as genome size, 16S rRNA gene copy number, and functional content of the genomes were related to their ubiquity and different environmental preferences of the corresponding taxa. The results showed clear correlations between genomic characteristics and environmental conditions. CONCLUSIONS: Ubiquity and adaptation were linked to genome size, while 16S copy number was not directly related to ubiquity. We observed that different combinations of these two characteristics delineate the different environments. Besides, the analysis of functional classes showed some clear signatures linked to particular environments.