Bacterial community assessment of drinking water and downstream distribution systems in highland localities of Ecuador.

Bacterial communities in drinking water provide a gauge to measure quality and confer insights into public health. In contrast to urban systems, water treatment in rural areas is not adequately monitored and could become a health risk. We performed 16S rRNA amplicon sequencing to analyze the microbiome present in the water treatment plants at two rural communities, one city, and the downstream water for human consumption in schools and reservoirs in the Andean highlands of Ecuador. We tested the effect of water treatment on the diversity and composition of bacterial communities. A set of physicochemical variables in the sampled water was evaluated and correlated with the structure of the observed bacterial communities. Predominant bacteria in the analyzed communities belonged to Proteobacteria and Actinobacteria. The Sphingobium genus, a chlorine resistance group, was particularly abundant. Of health concern in drinking water reservoirs were Fusobacteriaceae, Lachnospiraceae, and Ruminococcaceae; these families are associated with human and poultry fecal contamination. We propose the latter families as relevant biomarkers for establishing local standards for the monitoring of potable water systems in highlands of Ecuador. Our assessment of bacterial community composition in water systems in the Ecuadorian highlands provides a technical background to inform management decisions.

Harnessing microbial phylum-specific molecular markers for assessment of environmental estrogen degradation.

Steroidal estrogens are ubiquitous contaminants that have garnered attention worldwide due to their endocrine-disrupting and carcinogenic activities at sub-nanomolar concentrations. Microbial degradation is one of the main mechanisms through which estrogens can be removed from the environment. Numerous bacteria have been isolated and identified as estrogen degraders; however, little is known about their contribution to environmental estrogen removal. Here, our global metagenomic analysis indicated that estrogen degradation genes are widely distributed among bacteria, especially among aquatic actinobacterial and proteobacterial species. Thus, by using the Rhodococcus sp. strain B50 as the model organism, we identified three actinobacteria-specific estrogen degradation genes, namely aedGHJ, by performing gene disruption experiments and metabolite profile analysis. Among these genes, the product of aedJ was discovered to mediate the conjugation of coenzyme A with a unique actinobacterial C17 estrogenic metabolite, 5-oxo-4-norestrogenic acid. However, proteobacteria were found to exclusively adopt an α-oxoacid ferredoxin oxidoreductase (i.e., the product of edcC) to degrade a proteobacterial C18 estrogenic metabolite, namely 3-oxo-4,5-seco-estrogenic acid. We employed actinobacterial aedJ and proteobacterial edcC as specific biomarkers for quantitative polymerase chain reaction (qPCR) to elucidate the potential of microbes for estrogen biodegradation in contaminated ecosystems. The results indicated that aedJ was more abundant than edcC in most environmental samples. Our results greatly expand the understanding of environmental estrogen degradation. Moreover, our study suggests that qPCR-based functional assays are a simple, cost-effective, and rapid approach for holistically evaluating estrogen biodegradation in the environment.

Bacteriobiota of the Cave Church of Sts. Peter and Paul in Serbia-Culturable and Non-Culturable Communities' Assessment in the Bioconservation Potential of a Peculiar Fresco Painting.

The principal aim of this study was to determine bacterial diversity within the Cave Church of Sts. Peter and Paul, via culturable and non-culturable approaches, and elucidate the antifungal potential of autochthonous antagonistic bacterial isolates against biodeteriogenic fungi. Furthermore, whole-genome sequencing of selected bacterial antagonists and the analysis of genes included in the synthesis of secondary metabolites were performed. With the highest RA values, determined in metabarcoding analysis, phyla Actinobacteriota (12.08-54.00%) and Proteobacteria (25.34-44.97%) dominated most of the samples. A total of 44 different species, out of 96 obtained isolates, were determined as part of the culturable bacteriobiota, with the predominance of species from the genus Bacillus. Bacillus simplex was the only isolated species simultaneously present in all investigated substrata within the church. The best antagonistic activity against 10 biodeteriogenic fungi was documented for Streptomyces anulatus, followed by Bacillus altitudinis, Chryseobacterium viscerum, and Streptomyces sp. with their highest PGI% values ranging of from 55.9% to 80.9%. These promising results indicate that characterized bacteria are excellent candidates for developing biocontrol strategies for suppressing deteriogenic fungi responsible for the deterioration of investigated fresco painting. Finally, isolate 11-11MM, characterized as Streptomyces sp., represents a new species for science prompting the need for further study.

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil.

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing 13C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most 13C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed 13C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and 13C labeling (i.e., partial labeling or labeling at later stages). Major 13C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.IMPORTANCE Our study reveals the ecogenomic traits of microorganisms participating in the cellulose economy of soil. We identified three major categories of participants in this economy: (i) independent primary degraders, (ii) interdependent primary degraders, and (iii) secondary consumers (mutualists, opportunists, and parasites). Trade-offs between independent primary degraders, whose adaptations favor antagonism and competitive exclusion, and interdependent and secondary degraders, whose adaptations favor complex interspecies interactions, are expected to affect the fate of microbially processed carbon in soil. Our findings provide useful insights into the ecological relationships that govern one of the planet's most abundant resources of organic carbon. Furthermore, we demonstrate a novel gradient-resolved approach for stable isotope probing, which provides a cultivation-independent, genome-centric perspective into soil microbial processes.

Host Genetic and Environmental Factors Shape the Composition and Function of Gut Microbiota in Populations Living at High Altitude.

The human gut microbiota is affected by genetic and environmental factors. It remains unclear how host genetic and environmental factors affect the composition and function of gut microbiota in populations living at high altitudes. We used a metagenome-wide analysis to investigate the gut microbiota composition in 15 native Tibetans and 12 Hans living on the Tibetan Plateau. The composition of gut microbiota differed significantly between these two groups (P < 0.05). The Planctomycetes was the most abundant phyla both in native Tibetans and in Hans. Furthermore, the most relatively abundant phyla for native Tibetans were Bacteroidetes (15.66%), Firmicutes (11.10%), Proteobacteria (1.32%), Actinobacteria (1.10%), and Tenericutes (0.35%), while the most relatively abundant phyla for Hans were Bacteroidetes (16.28%), Firmicutes (8.41%), Proteobacteria (2.93%), Actinobacteria (0.49%), and Cyanobacteria (0.21%). The abundance of the majority of genera was significantly higher in Tibetans than in Hans (P < 0.01). The number of microbial genes was 4.9 times higher in Tibetans than in Hans. The metabolic pathways and clusters of orthologous groups differed significantly between the two populations (P < 0.05). The abundance of carbohydrate-active enzyme modules and antibiotic resistance genes was significantly lower in Tibetans compared to Hans (P < 0.05). Our results suggest that different genetic factors (race) and environmental factors (diets and consumption of antibiotics) may play important roles in shaping the composition and function of gut microbiota in populations living at high altitudes.

Ganoderma lucidum cultivation affect microbial community structure of soil, wood segments and tree roots.

The popular medicinal mushroom Ganoderma lucidum (Fr.) Karst. [Ling Zhi] has been widely used for the general promotion of health and longevity in Asian countries. Continuous cultivation may affect soil microbe and soil properties. However, the effect of G. lucidum cultivation on related wood segments, soil and tree roots microbial communities and soil properties is remain unknown. In our study, the microbial communities of soils, wood segments, and tree roots before and after G. lucidum cultivation were investigated by Illumina Miseq sequencing of both ITS and 16S rDNA, and taxonomic composition of eukaryotic and prokaryotic microorganisms were observed. Indices of microbial richness, diversity and evenness significantly differed between before and after G. lucidum cultivation. Each of the investigated sampling type harbored a distinctive microbial community and differed remarkably before and after G. lucidum cultivation. Ascomycota and Basidiomycota (fungi), Proteobacteria and Actinobacteria (bacteria) showed significant differences after Ling Zhi cultivation. The soil property values also changed after cultivation. The redundancy analysis (RDA) showed that both the fungal and bacterial community structure significantly correlated with soil humus, pH, nitrogen, carbon and trace elements (Fe, Zn, Mn, Cu) contents. The results indicated that G. lucidum cultivation may have significant differed the associated microbial community structures and soil properties. The study will provide useful information for G. lucidum cultivation and under-forest economic development.

Hup-Type Hydrogenases of Purple Bacteria: Homology Modeling and Computational Assessment of Biotechnological Potential.

Three-dimensional structures of six closely related hydrogenases from purple bacteria were modeled by combining the template-based and ab initio modeling approach. The results led to the conclusion that there should be a 4Fe3S cluster in the structure of these enzymes. Thus, these hydrogenases could draw interest for exploring their oxygen tolerance and practical applicability in hydrogen fuel cells. Analysis of the 4Fe3S cluster's microenvironment showed intragroup heterogeneity. A possible function of the C-terminal part of the small subunit in membrane binding is discussed. Comparison of the built models with existing hydrogenases of the same subgroup (membrane-bound oxygen-tolerant hydrogenases) was carried out. Analysis of intramolecular interactions in the large subunits showed statistically reliable differences in the number of hydrophobic interactions and ionic interactions. Molecular tunnels were mapped in the models and compared with structures from the PDB. Protein-protein docking showed that these enzymes could exchange electrons in an oligomeric state, which is important for oxygen-tolerant hydrogenases. Molecular docking with model electrode compounds showed mostly the same results as with hydrogenases from E. coli, H. marinus, R. eutropha, and S. enterica; some interesting results were shown in case of HupSL from Rba. sphaeroides and Rvi. gelatinosus.

An assessment of the microbial community in an urban fringing tidal marsh with an emphasis on petroleum hydrocarbon degradative genes.

Small fringing marshes are ecologically important habitats often impacted by petroleum. We characterized the phylogenetic structure (16S rRNA) and petroleum hydrocarbon degrading alkane hydroxylase genes (alkB and CYP 153A1) in a sediment microbial community from a New Hampshire fringing marsh, using alkane-exposed dilution cultures to enrich for petroleum degrading bacteria. 16S rRNA and alkB analysis demonstrated that the initial sediment community was dominated by Betaproteobacteria (mainly Comamonadaceae) and Gammaproteobacteria (mainly Pseudomonas), while CYP 153A1 sequences predominantly matched Rhizobiales. 24 h of exposure to n-hexane, gasoline, dodecane, or dilution culture alone reduced functional and phylogenetic diversity, enriching for Gammaproteobacteria, especially Pseudomonas. Gammaproteobacteria continued to dominate for 10 days in the n-hexane and no alkane exposed samples, while dodecane and gasoline exposure selected for gram-positive bacteria. The data demonstrate that small fringing marshes in New England harbor petroleum-degrading bacteria, suggesting that petroleum degradation may be an important fringing marsh ecosystem function.

Comparative study on the gut microbiotas of four economically important Asian carp species.

Gut microbiota of four economically important Asian carp species (silver carp, Hypophthalmichthys molitrix; bighead carp, Hypophthalmichthys nobilis; grass carp, Ctenopharyngodon idella; common carp, Cyprinus carpio) were compared using 16S rRNA gene pyrosequencing. Analysis of more than 590,000 quality-filtered sequences obtained from the foregut, midgut and hindgut of these four carp species revealed high microbial diversity among the samples. The foregut samples of grass carp exhibited more than 1,600 operational taxonomy units (OTUs) and the highest alpha-diversity index, followed by the silver carp foregut and midgut. Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria were the predominant phyla regardless of fish species or gut type. Pairwise (weighted) UniFrac distance-based permutational multivariate analysis of variance with fish species as a factor produced significant association (P<0.01). The gut microbiotas of all four carp species harbored saccharolytic or proteolytic microbes, likely in response to the differences in their feeding habits. In addition, extensive variations were also observed even within the same fish species. Our results indicate that the gut microbiotas of Asian carp depend on the exact species, even when the different species were cohabiting in the same environment. This study provides some new insights into developing commercial fish feeds and improving existing aquaculture strategies.

Pyrosequencing-based assessment of microbial community shifts in leachate from animal carcass burial lysimeter.

This study examined the use of microbial community structure as a bio-indicator of decomposition levels. High-throughput pyrosequencing technology was used to assess the shift in microbial community of leachate from animal carcass lysimeter. The leachate samples were collected monthly for one year and a total of 164,639 pyrosequencing reads were obtained and used in the taxonomic classification and operational taxonomy units (OTUs) distribution analysis based on sequence similarity. Our results show considerable changes in the phylum-level bacterial composition, suggesting that the microbial community is a sensitive parameter affected by the burial environment. The phylum classification results showed that Proteobacteria (Pseudomonas) were the most influential taxa in earlier decomposition stage whereas Firmicutes (Clostridium, Sporanaerobacter, and Peptostreptococcus) were dominant in later stage under anaerobic conditions. The result of this study can provide useful information on a time series of leachate profiles of microbial community structures and suggest patterns of microbial diversity in livestock burial sites. In addition, this result can be applicable to predict the decomposition stages under clay loam based soil conditions of animal livestock.

New Arsenate Reductase Gene (arrA) PCR Primers for Diversity Assessment and Quantification in Environmental Samples.

The extent of arsenic contamination in drinking water and its potential threat to human health have resulted in considerable research interest in the microbial species responsible for arsenic reduction. The arsenate reductase gene (arrA), an important component of the microbial arsenate reduction system, has been widely used as a biomarker to study arsenate-reducing microorganisms. A new primer pair was designed and evaluated for quantitative PCR (qPCR) and high-throughput sequencing of the arrA gene, because currently available PCR primers are not suitable for these applications. The primers were evaluated in silico and empirically tested for amplification of arrA genes in clones and for amplification and high-throughput sequencing of arrA genes from soil and groundwater samples. In silico, this primer pair matched (≥90% DNA identity) 86% of arrA gene sequences from GenBank. Empirical evaluation showed successful amplification of arrA gene clones of diverse phylogenetic groups, as well as amplification and high-throughput sequencing of independent soil and groundwater samples without preenrichment, suggesting that these primers are highly specific and can amplify a broad diversity of arrA genes. The arrA gene diversity from soil and groundwater samples from the Cache Valley Basin (CVB) in Utah was greater than anticipated. We observed a significant correlation between arrA gene abundance, quantified through qPCR, and reduced arsenic (AsIII) concentrations in the groundwater samples. Furthermore, we demonstrated that these primers can be useful for studying the diversity of arsenate-reducing microbial communities and the ways in which their relative abundance in groundwater may be associated with different groundwater quality parameters. IMPORTANCE: Arsenic is a major drinking water contaminant that threatens the health of millions of people worldwide. The extent of arsenic contamination and its potential threat to human health have resulted in considerable interest in the study of microbial species responsible for the reduction of arsenic, i.e., the conversion of AsV to AsIII In this study, we developed a new primer pair to evaluate the diversity and abundance of arsenate-reducing microorganisms in soil and groundwater samples from the CVB in Utah. We observed significant arrA gene diversity in the CVB soil and groundwater samples, and arrA gene abundance was significantly correlated with the reduced arsenic (AsIII) concentrations in the groundwater samples. We think that these primers are useful for studying the ecology of arsenate-reducing microorganisms in different environments.

Hydrocarbon degraders establish at the costs of microbial richness, abundance and keystone taxa after crude oil contamination in permafrost environments.

Oil spills from pipeline ruptures are a major source of terrestrial petroleum pollution in cold regions. However, our knowledge of the bacterial response to crude oil contamination in cold regions remains to be further expanded, especially in terms of community shifts and potential development of hydrocarbon degraders. In this study we investigated changes of microbial diversity, population size and keystone taxa in permafrost soils at four different sites along the China-Russia crude oil pipeline prior to and after perturbation with crude oil. We found that crude oil caused a decrease of cell numbers together with a reduction of the species richness and shifts in the dominant phylotypes, while bacterial community diversity was highly site-specific after exposure to crude oil, reflecting different environmental conditions. Keystone taxa that strongly co-occurred were found to form networks based on trophic interactions, that is co-metabolism regarding degradation of hydrocarbons (in contaminated samples) or syntrophic carbon cycling (in uncontaminated samples). With this study we demonstrate that after severe crude oil contamination a rapid establishment of endemic hydrocarbon degrading communities takes place under favorable temperature conditions. Therefore, both endemism and trophic correlations of bacterial degraders need to be considered in order to develop effective cleanup strategies.

Assessment of plant growth promoting bacterial populations in the rhizosphere of metallophytes from the Kettara mine, Marrakech.

Soil heavy metal contamination resulting from mining activities constitutes a major environmental problem worldwide. The spread of heavy metals is often facilitated by scarce vegetation cover, so there is an urgent need to improve plant survival and establishment in these metalliferous areas. This study is aimed at the isolation and analysis of the phylogenetic relationship of culturable bacteria from the rhizosphere of metallophyte plants growing in the Kettara mine, in Marrakech, in order to select plant growth-promoting rhizobacteria (PGPR), which could be used in assisted-phytoremediation. Bacterial isolates were grouped by random amplified polymorphic DNA analysis and identified by 16S rRNA gene sequencing. Strains were further characterized for the production of plant growth-promoting (PGP) substances, such as NH3, siderophores, indol-3-acetic acid (IAA), hydrogen cyanide, and extracellular enzymes, for ACC-deaminase activity, their capacity to solubilize phosphate, and for their tolerance to heavy metals and acidic pH. Rhizosphere soils were highly contaminated with Cu and Zn and presented low fertility. Phylogenetic analysis showed that the rhizobacteria were affiliated to three major groups: γ-Proteobacteria (48 %), ß-Proteobacteria (17 %), and Bacilli (17 %). The most represented genera were Pseudomonas (38 %), Bacillus (10 %), Streptomyces (10 %), and Tetrathiobacter (10 %). Overall, rhizobacterial strains showed an ability to produce multiple, important PGP traits, which may be helpful when applied as plant growth promoter agents in contaminated soils. PGPR were also able to withstand high levels of metals (up to 2615.2 mg Zn l-1, 953.29 mg Cu l-1, and 1124.6 mg Cd l-1) and the order of metal toxicity was Cd > Cu > Zn. The rhizobacterial strains isolated in the present study have the potential to be used as efficient bioinoculants in phytoremediation strategies for the recovery of Kettara mine soils.

Conservation analysis of the CydX protein yields insights into small protein identification and evolution.

BACKGROUND: The reliable identification of proteins containing 50 or fewer amino acids is difficult due to the limited information content in short sequences. The 37 amino acid CydX protein in Escherichia coli is a member of the cytochrome bd oxidase complex, an enzyme found throughout Eubacteria. To investigate the extent of CydX conservation and prevalence and evaluate different methods of small protein homologue identification, we surveyed 1095 Eubacteria species for the presence of the small protein. RESULTS: Over 300 homologues were identified, including 80 unannotated genes. The ability of both closely-related and divergent homologues to complement the E. coli ΔcydX mutant supports our identification techniques, and suggests that CydX homologues retain similar function among divergent species. However, sequence analysis of these proteins shows a great degree of variability, with only a few highly-conserved residues. An analysis of the co-variation between CydX homologues and their corresponding cydA and cydB genes shows a close synteny of the small protein with the CydA long Q-loop. Phylogenetic analysis suggests that the cydABX operon has undergone horizontal gene transfer, although the cydX gene likely evolved in a progenitor of the Alpha, Beta, and Gammaproteobacteria. Further investigation of cydAB operons identified two additional conserved hypothetical small proteins: CydY encoded in CydAQlong operons that lack cydX, and CydZ encoded in more than 150 CydAQshort operons. CONCLUSIONS: This study provides a systematic analysis of bioinformatics techniques required for the unique challenges present in small protein identification and phylogenetic analyses. These results elucidate the prevalence of CydX throughout the Proteobacteria, provide insight into the selection pressure and sequence requirements for CydX function, and suggest a potential functional interaction between the small protein and the CydA Q-loop, an enigmatic domain of the cytochrome bd oxidase complex. Finally, these results identify other conserved small proteins encoded in cytochrome bd oxidase operons, suggesting that small protein subunits may be a more common component of these enzymes than previously thought.

An assessment of the diversity of culturable bacteria from main root of sugar beet.

The partial sequences of the 16S rRNA genes of 531 bacteria isolated from the main root of the sugar beet (Beta vulgaris L.) were determined and subsequently grouped into 155 operational taxonomic units by clustering analysis (≥99% identity). The most abundant phylum was Proteobacteria (72.5-77.2%), followed by Actinobacteria (9.8-16.6%) and Bacteroidetes (4.3-15.4%). Alphaproteobacteria (46.7-64.8%) was the most dominant class within Proteobacteria. Four strains belonging to Verrucomicrobia were also isolated. Phylogenetic analysis revealed that the Verrucomicrobia bacterial strains were closely related to Haloferula or Verrucomicrobium.

Evolutionary insight into the functional amyloids of the pseudomonads.

Functional bacterial amyloids (FuBA) are important components in many environmental biofilms where they provide structural integrity to the biofilm, mediate bacterial aggregation and may function as virulence factor by binding specifically to host cell molecules. A novel FuBA system, the Fap system, was previously characterized in the genus Pseudomonas, however, very little is known about the phylogenetic diversity of bacteria with the genetic capacity to apply this system. Studies of genomes and public metagenomes from a diverse range of habitats showed that the Fap system is restricted to only three classes in the phylum Proteobacteria, the Beta-, Gamma- and Deltaproteobacteria. The structural organization of the fap genes into a single fapABCDEF operon is well conserved with minor variations such as a frequent deletion of fapA. A high degree of variation was seen within the primary structure of the major Fap fibril monomers, FapC, whereas the minor monomers, FapB, showed less sequence variation. Comparison of phylogenetic trees based on Fap proteins and the 16S rRNA gene of the corresponding bacteria showed remarkably similar overall topology. This indicates, that horizontal gene transfer is an infrequent event in the evolution of the Fap system.

C16S - a Hidden Markov Model based algorithm for taxonomic classification of 16S rRNA gene sequences.

Recent advances in high throughput sequencing technologies and concurrent refinements in 16S rDNA isolation techniques have facilitated the rapid extraction and sequencing of 16S rDNA content of microbial communities. The taxonomic affiliation of these 16S rDNA fragments is subsequently obtained using either BLAST-based or word frequency based approaches. However, the classification accuracy of such methods is observed to be limited in typical metagenomic scenarios, wherein a majority of organisms are hitherto unknown. In this study, we present a 16S rDNA classification algorithm, called C16S, that uses genus-specific Hidden Markov Models for taxonomic classification of 16S rDNA sequences. Results obtained using C16S have been compared with the widely used RDP classifier. The performance of C16S algorithm was observed to be consistently higher than the RDP classifier. In some scenarios, this increase in accuracy is as high as 34%. A web-server for the C16S algorithm is available at http://metagenomics.atc.tcs.com/C16S/.

Toward a more robust assessment of intraspecies diversity, using fewer genetic markers.

Phylogenetic sequence analysis of single or multiple genes has dominated the study and census of the genetic diversity among closely related bacteria. It remains unclear, however, how the results based on a few genes in the genome correlate with whole-genome-based relatedness and what genes (if any) best reflect whole-genome-level relatedness and hence should be preferentially used to economize on cost and to improve accuracy. We show here that phylogenies of closely related organisms based on the average nucleotide identity (ANI) of their shared genes correspond accurately to phylogenies based on state-of-the-art analysis of their whole-genome sequences. We use ANI to evaluate the phylogenetic robustness of every gene in the genome and show that almost all core genes, regardless of their functions and positions in the genome, offer robust phylogenetic reconstruction among strains that show 80 to 95% ANI (16S rRNA identity, >98.5%). Lack of elapsed time and, to a lesser extent, horizontal transfer and recombination make the selection of genes more critical for applications that target the intraspecies level, i.e., strains that show >95% ANI according to current standards. A much more accurate phylogeny for the Escherichia coli group was obtained based on just three best-performing genes according to our analysis compared to the concatenated alignment of eight genes that are commonly employed for phylogenetic purposes in this group. Our results are reproducible within the Salmonella, Burkholderia, and Shewanella groups and therefore are expected to have general applicability for microevolution studies, including metagenomic surveys.

Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified.

BACKGROUND: In recent years, model based approaches such as maximum likelihood have become the methods of choice for constructing phylogenies. A number of authors have shown the importance of using adequate substitution models in order to produce accurate phylogenies. In the past, many empirical models of amino acid substitution have been derived using a variety of different methods and protein datasets. These matrices are normally used as surrogates, rather than deriving the maximum likelihood model from the dataset being examined. With few exceptions, selection between alternative matrices has been carried out in an ad hoc manner. RESULTS: We start by highlighting the potential dangers of arbitrarily choosing protein models by demonstrating an empirical example where a single alignment can produce two topologically different and strongly supported phylogenies using two different arbitrarily-chosen amino acid substitution models. We demonstrate that in simple simulations, statistical methods of model selection are indeed robust and likely to be useful for protein model selection. We have investigated patterns of amino acid substitution among homologous sequences from the three Domains of life and our results show that no single amino acid matrix is optimal for any of the datasets. Perhaps most interestingly, we demonstrate that for two large datasets derived from the proteobacteria and archaea, one of the most favored models in both datasets is a model that was originally derived from retroviral Pol proteins. CONCLUSION: This demonstrates that choosing protein models based on their source or method of construction may not be appropriate.