Toward an efficient method of identifying core genes for evolutionary and functional microbial phylogenies

Characteristics and phylogenetic distribution of megaplasmids and prediction of a putative chromid in Pseudomonas aeruginosa

Research on megaplasmids that contribute to the spread of antimicrobial resistance (AMR) in Pseudomonas aeruginosa strains has grown in recent years due to the now widely used technologies allowing long-read sequencing. Here, we systematically analyzed distinct and consistent genetic characteristics of megaplasmids found in P. aeruginosa. Our data provide information on their phylogenetic distribution and hypotheses tracing the potential evolutionary paths of megaplasmids. Most of the megaplasmids we found belong to the IncP-2-type, with conserved and syntenic genetic backbones carrying modules of genes associated with chemotaxis apparatus, tellurite resistance and plasmid replication, segregation, and transmission. Extensively variable regions harbor abundant AMR genes, especially those encoding β-lactamases such as VIM-2, IMP-45, and KPC variants, which are high-risk elements in nosocomial infection. IncP-2 megaplasmids act as effective vehicles transmitting AMR genes to diverse regions. One evolutionary model of the origin of megaplasmids claims that chromids can develop from megaplasmids. These chromids have been characterized as an intermediate between a megaplasmid and a chromosome, also containing core genes that can be found on the chromosome but not on the megaplasmid. Using in silico prediction, we identified the "PABCH45 unnamed replicon" as a putative chromid in P. aeruginosa, which shows a much higher similarity and closer phylogenetic relationship to chromosomes than to megaplasmids while also encoding plasmid-like partition genes. We propose that such a chromid could facilitate genome expansion, allowing for more rapid adaptations to novel ecological niches or selective conditions, in comparison to megaplasmids.

Characterization of meningitis-causing bacteria, with focus on genomic and pangenomic study of multi-drug resistant Streptococcus pneumoniae from cerebrospinal fluid

Streptococcus pneumoniae is a major cause of meningitis in under developed countries with low vaccination rates and high antibiotic resistance. This study aimed to analyze 83 suspected meningitis patients in Karachi for the detection of S. pneumoniae followed by its whole genome sequencing and Pan Genome analysis. Out of the 83 samples collected, 33 samples with altered physical (turbidity), cytological (white blood cell count) and biochemical (total protein and total glucose concentrations) parameters indicated potential meningitis cases, while these parameters were within normal healthy ranges in remaining 50 samples. Latex particle agglutination (LPA) was performed on the 33 samples, revealing 20 positive cases of bacterial meningitis. The PCR and culturing methods revealed 5 S. pneumoniae isolates. Antibiotic susceptibility tests showed that one S. pneumoniae strain was resistant to erythromycin, levofloxacin, and tetracycline. Whole-genome sequencing of this resistant strain was performed and S. pneumoniae was confirmed with MLST analysis, while it had > 2.3 Mb genome and a single repUS43 plasmid. In CARD analysis, the strain had tet(M), ermB, RlmA(II), patB, pmrA, and patA ARGs, which could provide resistance against tetracycline, macrolide, fluoroquinolone, and glycopeptide antibiotics. Phylogenetic analysis revealed that the isolate was closely related to strains from Hungary and the USA. Pan-genome analysis with 144 genome assemblies from NCBI database showed that 1101 non-redundant core genes were shared between all strains. This study gives valuable understanding into the prevalence and characterization of meningitis-causing bacteria in Karachi, Pakistan  with prime focus on multi-drug resistant S. pneumoniae.

Effects of swine manure dilution with lagoon effluent on microbial communities and odor formation in pit recharge systems

Pit recharge systems (PRS) control odor by managing organic solids in swine manure. However, there needs to be more understanding of PRS's effect on the microbiome composition and its impact on odor formation. A study was conducted to understand how recharge intervals used in PRS impact manure microbiome and odor formation. Bioreactors dynamically loaded simulated recharge intervals of 14, 10, and 4 days by diluting swine manure with lagoon effluent at varying ratios. Treatment ratios tested included 10:0 (control), 7:3 (typical Korean PRS), 5:5 (enhanced PRS #1), and 2:8 (enhanced PRS #2). Manure microbial membership, chemical concentrations, and odorant concentrations were used to identify the interactions between microbiota, manure, and odor. The initial microbial community structure was controlled by dilution ratio and manure barn source material. Firmicutes and Proteobacteria were the dominant microbial phyla in manure and lagoon effluent, respectively, and significantly decreased or increased with dilution. Key microbial species were Clostridium saudiense in manure and Pseudomonas caeni in lagoon effluent. Percentages of these species declined by 8.9% or increased by 17.6%, respectively, with each unit dilution. Microbial community composition was controlled by both treatment (i.e., manure dilution ratio and barn source material) and environmental factors (i.e., solids and pH). Microbiome composition was correlated with manure odor formation profiles, but this effect was inseparable from environmental factors, which explained over 75% of the variance in odor profiles. Consequently, monitoring solids and pH in recharge waters will significantly impact odor control in PRS.

Physical Exercise-Induced DNA Methylation in Disease-Related Genes in Healthy Adults-A Systematic Review With Bioinformatic Analysis

ABSTRACT

Vasileva, F, Hristovski, R, Font-Lladó, R, Georgiev, G, Sacot, A, López-Ros, V, Calleja-González, J, Barretina-Ginesta, J, López-Bermejo, A, and Prats-Puig, A. Physical exercise-induced DNA methylation in disease-related genes in healthy adults-A systematic review with bioinformatic analysis. J Strength Cond Res 38(2): 384-393, 2024-This study aimed to systematically review the existing literature regarding physical exercise (PE) and DNA methylation (DNAm) in healthy adults. Specific goals were to (a) identify differently methylated genes (DMGs) after PE intervention, their imprinting status, chromosome and genomic location, function, and related diseases; and (b) to screen for core genes and identify methylation changes of the core genes that can be modified by PE intervention. Our search identified 2,869 articles from which 8 were finally included. We identified 1851 DMGs ( p < 0.05) after PE intervention, although 45 of them were imprinted. Aerobic exercise (AE) seems to induce more DNA hypermethylation rather than hypomethylation, whereas anaerobic exercise (AN) seems to induce more DNA hypomethylation rather than hypermethylation. Aerobic exercise induced highest % of methylation changes on chromosome 6, whereas AN and mixed type (MT) on chromosome 1. Mixed type induced higher % of methylation changes close to transcription start site in comparison to AE and AN. After PE intervention, DMGs were mainly involved in fat metabolism, cell growth, and neuronal differentiation, whereas diseases regulated by those genes were mainly chronic diseases (metabolic, cardiovascular, neurodegenerative). Finally, 19 core genes were identified among DMGs, all related to protein metabolism. In conclusion, our findings may shed some light on the mechanisms explaining PE-induced health benefits such as the potential role that PE-induced DNAm may have in disease prevention and disease treatment.

Microbial signature of plaque and gut in acute coronary syndrome

Gut microbiota is an emerging editable cardiovascular risk factor. We aim to investigate gut and coronary plaque microbiota, using fecal samples and angioplasty balloons from patients with acute coronary syndrome (ACS), chronic coronary syndrome (CCS) and control subjects. We examined bacterial communities in gut and coronary plaques by 16S rRNA sequencing and we performed droplet digital PCR analysis to investigate the gut relative abundance of the bacterial genes CutC/CntA involved in trimethylamine N-oxide synthesis. Linear discriminant analysis effect size (LEfSe) at the genus and species levels displayed gut enrichment in Streptococcus, Granulicatella and P. distasonis in ACS compared with CCS and controls; Roseburia, C. aerofaciens and F. prausnitzii were more abundant in controls than in patients. Principal component analysis (PCA) of 41 differentially abundant gut taxa showed a clustering of the three groups. In coronary plaque, LEfSe at the genus level revealed an enrichment of Staphylococcus and Streptococcus in ACS, and Paracoccus in CCS, whereas PCA of 15 differentially abundant plaque taxa exhibited clustering of ACS and CCS patients. CutC and CntA genes were more abundant in ACS and CCS than in controls while no significant difference emerged between ACS and CCS. Our results indicate that ACS and CCS exhibit a different gut and plaque microbial signature, suggesting a possible role of these microbiotas in coronary plaque instability.

UACG: Up-to-Date Archaeal Core Genes and Software for Phylogenomic Tree Reconstruction

In the post-genomic era, phylogenomics is a powerful and routinely-used tool to discover evolutionary relationships between microorganisms. Inferring phylogenomic trees by concatenating core gene sequences into a supermatrix is the standard method. The previously released up-to-date bacterial core gene (UBCG) tool provides a pipeline to infer phylogenomic trees using single-copy core genes for the Bacteria domain. In this study, we established up-to-date archaeal core gene (UACG), comprising 128 genes suitable for inferring archaeal phylogenomic trees. To test the gene set, we selected the Haloarcula genus and scrutinized its phylogeny. The phylogeny inferred using the UACG tool was consistent with the orthoANIu dendrogram, whereas the 16S rRNA gene phylogeny showed high intragenomic heterogeneity resulting in phylogenetic discrepancies. The software tool using the UACG set is available at https://www.ezbiocloud.net/tools/uacg .

Widely targeted metabolomic, transcriptomic, and metagenomic profiling reveal microbe-plant-metabolic reprogramming patterns mediated by Streptomyces pactum Act12 enhance the fruit quality of Capsicum annuum L

Plant growth-promoting rhizobacteria, such as Streptomyces pactum Act12, promote crop growth and stress resistance, but their contribution to fruit quality is still poorly understood. Herein we conducted a field experiment to ascertain the effects of S. pactum Act12-mediated metabolic reprogramming and underlying mechanisms in pepper (Capsicum annuum L.) fruit based on widely targeted metabolomic and transcriptomic profiling. We additionally performed metagenomic analysis to elucidate the potential relationship between S. pactum Act12-mediated reshaping of rhizosphere microbial communities and pepper fruit quality. Soil inoculation with S. pactum Act12 considerably increased the accumulation of capsaicinoids, carbohydrates, organic acids, flavonoids, anthraquinones, unsaturated fatty acids, vitamins, and phenolic acids in pepper fruit samples. Consequently, fruit flavor, taste, and color were modified, accompanied by elevated contents of nutrients and bioactive compounds. Increased microbial diversity and recruitment of potentially beneficial taxa were observed in inoculated soil samples, with crosstalk between microbial gene functions and pepper fruit metabolism. The reformed structure and function of rhizosphere microbial communities were closely associated with pepper fruit quality. Our findings indicate that S. pactum Act12-mediated interactions between rhizosphere microbial communities and pepper plants are responsible for intricate fruit metabolic reprogramming patterns, which enhance not only overall fruit quality but also consumer acceptability.

Contribution of pollution gradient to the sediment microbiome and potential pathogens in urban streams draining into Lake Victoria (Kenya)

In sub-Saharan Africa (SSA), urban rivers/streams have long been subjected to anthropogenic pollution caused by urbanization, resulting in significantly altered chemical and biological properties of surface water and sediments. However, little is known about the diversity and structure of river microbial community composition and pathogens, as well as how they respond to anthropogenic inputs. High-throughput 16S rRNA amplicon sequencing and PICRUSt predictive function profiling were used in this study to conduct a comprehensive analysis of the spatial bacterial distribution and metabolic functions in sediment of two urban streams (Kisat and Auji) flowing through Kisumu City, Kenya. Results revealed that sediment samples from the highly urbanized mid and lower stream catchment zones of both streams had significantly higher levels of total organic carbon (TOC), total nitrogen (TN), total phosphorous (TP) than the less urbanized upper catchment zone, and were severely polluted with toxic heavy metals lead (Pb), cadmium (Cd), and copper (Cu). Differential distribution of Actinobacteria, Proteobacteria, Chloroflexi, and Verrucomicrobia in sediment bacterial composition was detected along stream catchment zones. The polluted mid and lower catchment zones were rich in Actinobacteria and Proteobacteria, as well as a variety of potential pathogenic taxa such as Corynebacterium, Staphylococcus, Cutibacterium, Turicella, Acinetobacter, and Micrococcus, as well as enteric bacteria such as Faecalibacterium, Shewanella, Escherichia, Klebsiella, Enterococcus, Prevotella, Legionella, Vibrio and Salmonella. Furthermore, PICRUSt metabolic inference analysis revealed an increasing enrichment in the sediments of genes associated with carbon and nitrogen metabolism, disease pathogenesis, and virulence. Environmental factors (TOC, Pb, Cd, TN, pH) and geographical distance as significant drivers of sediment bacterial community assembly, with the environmental selection to play a dominant role. In polluted river catchment zone sediment samples, Pb content was the most influential sediment property, followed by TOC and Cd content. Given the predicted increase in urbanization in SSA, further alteration of surface water and sediment microbiome due to urban river pollution is unavoidable, with potential long-term effects on ecosystem function and potential health hazards. As a result, this study provides valuable information for ecological risk assessment and management of urban rivers impacted by diffuse and point source anthropogenic inputs, which is critical for future proactive and sustainable urban waste management, monitoring, and water pollution control in low-income countries.

Low-Diversity Microbiota in Apical Periodontitis and High Blood Pressure Are Signatures of the Severity of Apical Lesions in Humans

(1) Background: In developed countries, the prevalence of apical periodontitis (AP) varies from 20% to 50% for reasons that could be associated with the apical periodontitis microbiota ecology. (2) Methods: We performed a clinical study in the Odontology department of Toulouse hospital in France, to sequence the 16S rRNA gene of AP microbiota and collect clinical parameters from 94 patients. Forty-four patients were characterized with a PAI (periapical index of AP severity) score lower or equal to 3, while the others had superior scores (n = 50). (3) Results: The low diversity of granuloma microbiota is associated with the highest severity (PAI = 5) of periapical lesions (Odds Ratio 4.592, IC 95% [1.6329; 14.0728]; p = 0.001; notably, a lower relative abundance of Burkholderiaceae and a higher relative abundance of Pseudomonas and Prevotella). We also identified that high blood pressure (HBP) is associated with the increase in PAI scores. (4) Conclusions: Our data show that a low diversity of bacterial ecology of the AP is associated with severe PAI scores, suggesting a causal mechanism. Furthermore, a second risk factor was blood pressure associated with the severity of apical periodontitis.

Funneliformis mosseae Inoculation Enhances Cucurbita pepo L. Plant Growth and Fruit Yield by Reshaping Rhizosphere Microbial Community Structure

Arbuscular mycorrhizal fungi (AMF) are essential components of the soil microbiome that can facilitate plant growth and enhance abiotic and biotic stress resistance. However, the mechanisms via which AMF inoculation influences Cucurbita pepo L. plant growth and fruit yield remain unclear. Here, we conducted pot experiments to investigate bacterial and fungal community structure in the rhizosphere of C. pepo plants inoculated with Funneliformis mosseae (Nicoll. & Gerd.) Gerd. & Trappe based on 16S ribosomal RNA and internal transcribed spacer gene sequencing. The α-diversity of bacteria increased significantly following F. mosseae inoculation, whereas the α-diversity of fungi exhibited an opposite trend (p < 0.01). The relative abundances of major bacterial phyla, Actinobacteria, Acidobacteria, and Chloroflexi, together with the fungal phylum Ascomycota, were all higher in inoculated samples than in uninoculated controls. F. mosseae inoculation led to remarkable enrichment of potentially beneficial taxa (e.g., Streptomyces, Sphingomonas, Lysobacter, and Trichoderma), in stark contrast to depletion of fungal pathogens (e.g., Botryotrichum, Acremonium, Fusarium, and Plectosphaerella). Pathways related to amino acid metabolism and antibiotic biosynthesis were upregulated by F. mosseae inoculation, whereas pathways involved in infectious diseases were downregulated. The results suggest that F. mosseae inoculation reshapes the rhizosphere microbiome, thereby augmenting C. pepo plant growth and fruit yield.

Pan-genome evolution and its association with divergence of metabolic functions in Bifidobacterium genus

Previous studies were mainly focused on genomic evolution and diversity of type species of Bifidobacterium genus due to their health-promoting effect on host. However, those studies were mainly based on species-level taxonomic resolution, adaptation, and characterization of carbohydrate metabolic features of the bifidobacterial species. Here, a comprehensive analysis of the type strain genome unveils the association of pan-genome evolution with the divergence of metabolic function of the Bifidobacterium genus. This study has also demonstrated that horizontal gene transfer, as well as genome expansion and reduction events, leads to the divergence of metabolic functions in Bifidobacterium genus. Furthermore, the genome-based search of probiotic traits among all the available bifidobacterial type strains gives hints on type species, that could confer health benefits to nutrient-deficient individuals. Altogether, the present study provides insight into the developments of genomic evolution, functional divergence, and potential probiotic type species of the Bifidobacterium genus.

Exploration of the presence and abundance of multidrug resistance efflux genes in oil and gas environments

As sequencing technology improves and the cost of metagenome sequencing decreases, the number of sequenced environments increases. These metagenomes provide a wealth of data in the form of annotated and unannotated genes. The role of multidrug resistance efflux pumps (MDREPs) is the removal of antibiotics, biocides and toxic metabolites created during aromatic hydrocarbon metabolism. Due to their naturally occurring role in hydrocarbon metabolism and their role in biocide tolerance, MDREP genes are of particular importance for the protection of pipeline assets. However, the heterogeneity of MDREP genes creates a challenge during annotation and detection. Here we use a selection of primers designed to target MDREPs in six pure species and apply them to publicly available metagenomes associated with oil and gas environments. Using in silico PCR with relaxed primer binding conditions we probed the metagenomes of a shale reservoir, a heavy oil tailings pond, a civil wastewater treatment, two marine sediments exposed to hydrocarbons following the Deepwater Horizon oil spill and a non-exposed marine sediment to assess the presence and abundance of MDREP genes. Through relaxed primer binding conditions during in silico PCR, the prevalence of MDREPs was determined. The percentage of nucleotide sequences identified by the MDREP primers was partially augmented by exposure to hydrocarbons in marine sediment and in shale reservoir compared to hydrocarbon-free marine sediments while tailings ponds and wastewater had the highest percentages. We believe this approach lays the groundwork for a supervised method of identifying poorly conserved genes within metagenomes.

Mapping Strengths and Weaknesses of Different Clustering Approaches to Deciphering Bacterial Chimerism

Bacterial genomes are chimeras of DNA of different ancestries. Deconstructing chimeric genomes is central to understanding the evolutionary trajectories of their disparate components and thus the organisms as a whole in the light of their evolutionary contexts. Of specific interest is to delineate and quantify native (vertically inherited) and alien (horizontally acquired) components of bacterial genomes and also specify genomic fractions that represent different donor sources. An agglomerative clustering procedure that prioritizes grouping of proximal similar genomic segments has previously been invoked for this purpose in conjunction with a recursive segmentation procedure. Surprisingly, however, the relative strengths and weaknesses of different clustering approaches to deciphering bacterial chimerism have not yet been investigated, despite the need to robustly interpret tens of thousands of completely sequenced bacterial genomes and nearly complete genome assemblies available in the public databases. To bridge this knowledge gap and develop more robust approaches, we assessed different clustering methods, including segment order based (proximal) clustering, hierarchical clustering, affinity propagation clustering, and a novel network clustering approach on chimeric genomes modeled after bacterial genomes representing a broad spectrum of compositional complexity. Although segment order-based clustering and network clustering compared favorably with the other approaches in discriminating between native and alien DNA at genome optimized settings, network clustering did consistently better than other methods at parametric settings optimized on all test genomes together. Segment order-based clustering and hierarchical clustering outperformed other methods in alien DNA identification while preserving donor identity in the genomes. Our study highlights the strengths and weaknesses of different approaches and suggests how this can be leveraged to achieve a more robust deconstruction of bacterial chimerism.

Gut microbiota dysbiosis of type 2 diabetic mice impairs the intestinal daily rhythms of GLP-1 sensitivity

The gut-brain-beta cell glucagon-like peptide-1 (GLP-1)-dependent axis and the clock genes both control insulin secretion. Evidence shows that a keystone of this molecular interaction could be the gut microbiota. We analyzed in mice the circadian profile of GLP-1 sensitivity on insulin secretion and the impact of the autonomic neuropathy, antibiotic treated in different diabetic mouse models and in germ-free colonized mice. We show that GLP-1sensitivity is maximal during the dark feeding period, i.e., the postprandial state. Coincidently, the ileum expression of GLP-1 receptor and peripherin is increased and tightly correlated with a subset of clock gene. Since both are markers of enteric neurons, it suggests a role in the gut-brain-beta cell GLP-1-dependent axis. We evaluated the importance of gut microbiota dysbiosis and found that the abundance of ileum bacteria, particularly Ruminococcaceae and Lachnospiraceae, oscillated diurnally, with a maximum during the dark period, along with expression patterns of a subset of clock genes. This diurnal pattern of circadian gene expression and Lachnospiraceae abundance was also observed in two separate mouse models of gut microbiota dysbiosis and of autonomic neuropathy with impaired GLP-1 sensitivity (1.high-fat diet-fed type 2 diabetic, 2.antibiotic-treated/germ-free mice). Our data show that GLP-1 sensitivity relies on specific pattern of intestinal clock gene expression and specific gut bacteria. This new statement opens opportunities to treat diabetic patient with GLP-1-based therapies by using on a possible pre/probiotic co-treatment to improve the time-dependent efficiency of these therapies.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

A Soybean Resistant Protein-Containing Diet Increased the Production of Reg3γ Through the Regulation of the Gut Microbiota and Enhanced the Intestinal Barrier Function in Mice

The maintenance of intestinal homeostasis is necessary for a good quality of life, and strengthening of the intestinal barrier function is thus an important issue. Therefore, we focused on soybean resistant protein (SRP) derived from kori-tofu (freeze-dried tofu), which is a traditional Japanese food, as a functional food component. In this study, to investigate the effect of SRP on the intestinal barrier function and intestinal microbiota, we conducted an SRP free intake experiment in mice. Results showed that ingestion of SRP decreased the serum level of lipopolysaccharide-binding protein and induced the expression of Reg3γ, thereby improving the intestinal barrier function. In addition, SRP intake induced changes in the cecal microbiota, as observed by changes in β-diversity. In particular, in the microbiota, the up-regulation of functional gene pathways related to the bacterial invasion of epithelial cells (ko05100) was observed, suggesting that Reg3γ expression was induced by the direct stimulation of epithelial cells. The results of this study suggest that SRP is a functional food component that may contribute to the maintenance of intestinal homeostasis.

Can functional genomic diversity provide novel insights into mechanisms of community assembly? A pilot study from an invaded alpine streambed

An important focus of community ecology, including invasion biology, is to investigate functional trait diversity patterns to disentangle the effects of environmental and biotic interactions. However, a notable limitation is that studies usually rely on a small and easy-to-measure set of functional traits, which might not immediately reflect ongoing ecological responses to changing abiotic or biotic conditions, including those that occur at a molecular or physiological level. We explored the potential of using the diversity of expressed genes-functional genomic diversity (FGD)-to understand ecological dynamics of a recent and ongoing alpine invasion. We quantified FGD based on transcriptomic data measured for 26 plant species occurring along adjacent invaded and pristine streambeds. We used an RNA-seq approach to summarize the overall number of expressed transcripts and their annotations to functional categories, and contrasted this with functional trait diversity (FTD) measured from a suite of characters that have been traditionally considered in plant ecology. We found greater FGD and FTD in the invaded community, independent of differences in species richness. However, the magnitude of functional dispersion was greater from the perspective of FGD than from FTD. Comparing FGD between congeneric alien-native species pairs, we did not find many significant differences in the proportion of genes whose annotations matched functional categories. Still, native species with a greater relative abundance in the invaded community compared with the pristine tended to express a greater fraction of genes at significant levels in the invaded community, suggesting that changes in FGD may relate to shifts in community composition. Comparisons of diversity patterns from the community to the species level offer complementary insights into processes and mechanisms driving invasion dynamics. FGD has the potential to illuminate cryptic changes in ecological diversity, and we foresee promising avenues for future extensions across taxonomic levels and macro-ecosystems.

Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3

Culture-independent analyses of microbial communities have progressed dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1262 metagenomes) and IBD (1635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.

Next Generation High Throughput Sequencing to Assess Microbial Communities: An Application Based on Water Quality

Traditional techniques to identify different contaminants (biological or chemical) in the waters are slow, laborious, and can require specialized expertise. Hence, the rapid determination of water quality using more sensitive and reliable metagenomic based approaches attains special importance. Metagenomics deals with the study of genetic material that is recovered from microbial communities present in environmental samples. In traditional techniques cultivation-based methodologies were used to describe the diversity of microorganisms in environmental samples. It has failed to function as a robust marker because of limited taxonomic and phylogenetic implications. In this backdrop, high-throughput DNA sequencing approaches have proven very powerful in microbial source tracking because of investigating the full variety of genome-based analysis such as microbial genetic diversity and population structure played by them. Next generation sequencing technologies can reveal a greater proportion of microbial communities that have not been reported earlier by traditional techniques. The present review highlights the shift from traditional techniques for the basic study of community composition to next-generation sequencing (NGS) platforms and their potential applications to the biomonitoring of water quality in relation to human health.

Plant flavones enrich rhizosphere Oxalobacteraceae to improve maize performance under nitrogen deprivation

Beneficial interactions between plant roots and rhizosphere microorganisms are pivotal for plant fitness. Nevertheless, the molecular mechanisms controlling the feedback between root architecture and microbial community structure remain elusive in maize. Here, we demonstrate that transcriptomic gradients along the longitudinal root axis associate with specific shifts in rhizosphere microbial diversity. Moreover, we have established that root-derived flavones predominantly promote the enrichment of bacteria of the taxa Oxalobacteraceae in the rhizosphere, which in turn promote maize growth and nitrogen acquisition. Genetic experiments demonstrate that LRT1-mediated lateral root development coordinates the interactions of the root system with flavone-dependent Oxalobacteraceae under nitrogen deprivation. In summary, these experiments reveal the genetic basis of the reciprocal interactions between root architecture and the composition and diversity of specific microbial taxa in the rhizosphere resulting in improved plant performance. These findings may open new avenues towards the breeding of high-yielding and nutrient-efficient crops by exploiting their interaction with beneficial soil microorganisms.

Mutual environmental drivers of the community composition, functional attributes and co-occurrence patterns of bacterioplankton in the composite aquatic ecosystem of Taihu watershed in China

This study aimed to determine the environmental and ecological factors influencing the planktonic prokaryotic community profiles in the composite ecosystem comprising Taihu Lake, Taipu River and Jinze Reservoir in the Taihu Watershed in China. A total of 42 water samples were intermittently collected from different sites in 6 months across four seasons. Physicochemical characteristics of the ecosystem, bacterioplankton diversity and composition, the presence of co-occurrence patterns, and environmental predictors of ecological modules in the bacterioplankton network were determined. The central species played a more important role in regulating the structure and function of the bacterioplankton community and in responding to environmental contamination than the entire community. The relative abundance of the phylum Proteobacteria and the class Betaproteobacteria varied significantly between months and locations, which were identified as core functional taxa. A non-random co-occurrence pattern and function-driven modular structure were observed in the bacterioplankton co-occurrence network. Dissolved oxygen and ammonium nitrogen were the major and mutual environmental predictors of the bacterioplankton community composition, functional attributes and relative abundance of ecological modules. The results improve our understanding of the impact of anthropogenic contamination on bacterioplankton diversity and biogeochemical cycles and the formulation of strategies for bioremediation of the Taihu Watershed.

The Pediatric Obesity Microbiome and Metabolism Study (POMMS): Methods, Baseline Data, and Early Insights

OBJECTIVE

The purpose of this study was to establish a biorepository of clinical, metabolomic, and microbiome samples from adolescents with obesity as they undergo lifestyle modification.

METHODS

A total of 223 adolescents aged 10 to 18 years with BMI ≥95th percentile were enrolled, along with 71 healthy weight participants. Clinical data, fasting serum, and fecal samples were collected at repeated intervals over 6 months. Herein, the study design, data collection methods, and interim analysis-including targeted serum metabolite measurements and fecal 16S ribosomal RNA gene amplicon sequencing among adolescents with obesity (n = 27) and healthy weight controls (n = 27)-are presented.

RESULTS

Adolescents with obesity have higher serum alanine aminotransferase, C-reactive protein, and glycated hemoglobin, and they have lower high-density lipoprotein cholesterol when compared with healthy weight controls. Metabolomics revealed differences in branched-chain amino acid-related metabolites. Also observed was a differential abundance of specific microbial taxa and lower species diversity among adolescents with obesity when compared with the healthy weight group.

CONCLUSIONS

The Pediatric Metabolism and Microbiome Study (POMMS) biorepository is available as a shared resource. Early findings suggest evidence of a metabolic signature of obesity unique to adolescents, along with confirmation of previously reported findings that describe metabolic and microbiome markers of obesity.

Exploiting the Microbiota for the Diagnosis of Anal Precancerous Lesions in Men Who Have Sex With Men

BACKGROUND

While the microbiota has been associated with HPV malignant transformation, it is unclear whether anal bacteria could improve the low specificity of anal cytology for the screening of high grade intraepithelial squamous neoplasia (HSIL).

METHODOLOGY

We recruited MSM undergoing anal cytology and high-resolution anoscopy. We assessed the microbiota composition from fecal samples and cytobrush anal samples using 16SrDNA sequencing in subjects with and without biopsy-proven HSIL (bHSIL). We selected bacterial biomarkers based on their linear discriminant analysis (LDA). We assessed their predictive performance using logistic regression and bootstrap resampling.

RESULTS

We included 128 individuals, 47 (36.7%) with bHSIL and 99 (77.3%) with HIV. We detected 40 potential predictors of bHSIL. Ruminococcaceae NK4A214 group, Alloprevotella genus, Prevotella melanonigenica and Ruminococcaceae UCG-014 were the most predictive of bHSIL. From 35 false-positive cytologic results, the combination of these four biomarkers with the anal cytology reclassified to true negative 33 (94%) individuals and showed good diagnostic performance (AUC 0.805, 95%CI 0.728 - 0.882).

CONCLUSIONS

We found anal-associated bacteria indicative of a higher risk of precancerous anal lesions, which combination was highly specific. The microbiota could be developed as a complementary diagnostic tool to overcome the limitations of the current screening strategy for anal cancer.

Comparative genomic analysis reveals metabolic diversity of different Paenibacillus groups

The genus Paenibacillus was originally recognized based on the 16S rRNA gene phylogeny. Recently, a standardized bacterial taxonomy approach based on a genome phylogeny has substantially revised the classification of Paenibacillus, dividing it into 23 genera. However, the metabolic differences among these groups remain undescribed. Here, genomes of 41 Paenibacillus strains comprising 25 species were sequenced, and a comparative genomic analysis was performed considering these and 187 publicly available Paenibacillus genomes to understand their phylogeny and metabolic differences. Phylogenetic analysis indicated that Paenibacillus clustered into 10 subgroups. Core genome and pan-genome analyses revealed similar functional categories among the different Paenibacillus subgroups; however, each group tended to harbor specific gene families. A large proportion of genes in the subgroups A, E, and G are related to carbohydrate metabolism. Among them, genes related to the glycoside hydrolase family were most abundant. Metabolic reconstruction of the newly sequenced genomes showed that the Embden-Meyerhof-Parnas pathway, pentose phosphate pathway, and citric acid cycle are central pathways of carbohydrate metabolism in Paenibacillus. Further, the genomes of the subgroups A and G lack genes involved in glyoxylate cycle and D-galacturonate degradation, respectively. The current study revealed the metabolic diversity of Paenibacillus subgroups assigned based on a genomic phylogeny and could inform the taxonomy of Paenibacillus. KEY POINTS: • Paenibacillus clustered into 10 subgroups. • Genomic content variation and metabolic diversity in the subgroup A, E, and G were described. • Carbohydrate transport and metabolism is important for Paenibacillus survival.

Nutrition, Microbiota and Role of Gut-Brain Axis in Subjects with Phenylketonuria (PKU): A Review

The composition and functioning of the gut microbiota, the complex population of microorganisms residing in the intestine, is strongly affected by endogenous and exogenous factors, among which diet is key. Important perturbations of the microbiota have been observed to contribute to disease risk, as in the case of neurological disorders, inflammatory bowel disease, obesity, diabetes, cardiovascular disease, among others. Although mechanisms are not fully clarified, nutrients interacting with the microbiota are thought to affect host metabolism, immune response or disrupt the protective functions of the intestinal barrier. Similarly, key intermediaries, whose presence may be strongly influenced by dietary habits, sustain the communication along the gut-brain-axis, influencing brain functions in the same way as the brain influences gut activity. Due to the role of diet in the modulation of the microbiota, its composition is of high interest in inherited errors of metabolism (IEMs) and may reveal an appealing therapeutic target. In IEMs, for example in phenylketonuria (PKU), since part of the therapeutic intervention is based on chronic or life-long tailored dietetic regimens, important variations of the microbial diversity or relative abundance have been observed. A holistic approach, including a healthy composition of the microbiota, is recommended to modulate host metabolism and affected neurological functions.

Characteristics of microbial community of soil subjected to industrial production of antibiotics

Ecosystems worldwide are exposed to pollutants connected to the industrial production of pharmaceuticals. The objective of this study was to study the composition and characteristics of the soil microbial communities that had been exposed to long-term selection pressure caused by the industrial production of penicillin G. Soil samples from four sites among the penicillin G production plant were analysed using 16S rRNA profiling via Illumina MiSeq platform and were compared with the control samples from four sites outside the plant. Total metagenomic DNA from the impacted soil was also used for the preparation of E. coli T1R-based fosmid library which was consequently qualitatively tested for the presence of penicillin G acylase (PGA)-encoding genes using the method of sequence homology. Analyses of alpha diversity revealed that the long-term antibiotic presence in the soil significantly increased the microbial diversity and richness in terms of Shannon diversity index (p = 0.002) and Chao estimates (p = 0.004). Principal component analysis showed that the two types of communities (on-site and control) could be separated at the phylum, class and genus level. The on-site soil was enriched in Betaproteobacteria, Deltaproteobacteria, Gemmatimonadetes, Acidobacteria and Planctomycetia, while a significant decrease in Actinobacteria was observed. Metagenomic fosmid library revealed high hit rates in identifying PGAs (14 different genes identified) and confirmed the biotechnological potential of soils impacted by anthropogenic activity. This study offers new insights into the changes in microbial communities of soils exposed to anthropogenic activity as well as indicates that those soils may represent a hotspot for biotechnologically interesting targets.

NOD1 deficiency promotes an imbalance of thyroid hormones and microbiota homeostasis in mice fed high fat diet

The contribution of the nucleotide-binding oligomerization domain protein NOD1 to obesity has been investigated in mice fed a high fat diet (HFD). Absence of NOD1 accelerates obesity as early as 2 weeks after feeding a HFD. The obesity was due to increases in abdominal and inguinal adipose tissues. Analysis of the resting energy expenditure showed an impaired function in NOD1-deficient animals, compatible with an alteration in thyroid hormone homeostasis. Interestingly, free thyroidal T4 increased in NOD1-deficient mice fed a HFD and the expression levels of UCP1 in brown adipose tissue were significantly lower in NOD1-deficient mice than in the wild type animals eating a HFD, thus contributing to the observed adiposity in NOD1-deficient mice. Feeding a HFD resulted in an alteration of the proinflammatory profile of these animals, with an increase in the infiltration of inflammatory cells in the liver and in the white adipose tissue, and an elevation of the circulating levels of TNF-α. In addition, alterations in the gut microbiota in NOD1-deficient mice correlate with increased vulnerability of their ecosystem to the HFD challenge and affect the immune-metabolic phenotype of obese mice. Together, the data are compatible with a protective function of NOD1 against low-grade inflammation and obesity under nutritional conditions enriched in saturated lipids. Moreover, one of the key players of this early obesity onset is a dysregulation in the metabolism and release of thyroid hormones leading to reduced energy expenditure, which represents a new role for these hormones in the metabolic actions controlled by NOD1.

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.

Behçet's Disease Under Microbiotic Surveillance? A Combined Analysis of Two Cohorts of Behçet's Disease Patients

Background: In Behçet's disease (BD), an auto-inflammatory vasculitis, an unbalanced gut microbiota can contribute to pro-inflammatory reactions. In separate studies, distinct pro- and anti-inflammatory bacteria associated with BD have been identified.

Methods: To establish disease-associated determinants, we performed gut microbiome profiling in BD patients from the Netherlands (n = 19) and Italy (n = 13), matched healthy controls (HC) from the Netherlands (n = 17) and Italy (n = 15) and oral microbiome profiling in Dutch BD patients (n = 18) and HC (n = 15) by 16S rRNA gene sequencing. In addition, we used fecal IgA-SEQ analysis to identify specific IgA coated bacterial taxa in Dutch BD patients (n = 13) and HC (n = 8).

Results: In BD stool samples alpha-diversity was conserved, whereas beta-diversity analysis showed no clustering based on disease, but a significant segregation by country of origin. Yet, a significant decrease of unclassified Barnesiellaceae and Lachnospira genera was associated with BD patients compared to HC. Subdivided by country, the Italian cohort displays a significant decrease of unclassified Barnesiellaceae and Lachnospira genera, in the Dutch cohort this decrease is only a trend. Increased IgA-coating of Bifidobacterium spp., Dorea spp. and Ruminococcus bromii species was found in stool from BD patients. Moreover, oral Dutch BD microbiome displayed increased abundance of Spirochaetaceae and Dethiosulfovibrionaceae families.

Conclusions: BD patients show decreased fecal abundance of Barnesiellaceae and Lachnospira and increased oral abundance of Spirochaetaceae and Dethiosulfovibrionaceae. In addition, increased fecal IgA coating of Bifidobacterium, Ruminococcus bromii and Dorea may reflect retention of anti-inflammatory species and neutralization of pathosymbionts in BD, respectively. Additional studies are warranted to relate intestinal microbes with the significance of ethnicity, diet, medication and response with distinct pro- and inflammatory pathways in BD patients.

Ecological and Technical Mechanisms for Cross-Reaction of Human Fecal Indicators with Animal Hosts

Quantitative PCR (qPCR) assays for human/sewage marker genes have demonstrated sporadic positive results in animal feces despite their high specificities to sewage and human feces. It is unclear whether these positive reactions are caused by true occurrences of microorganisms containing the marker gene (i.e., indicator organisms) or nonspecific amplification (false positive). The distribution patterns of human/sewage indicator organisms in animals have not been explored in depth, which is crucial for evaluating a marker gene's true- or false-positive reactions. Here, we analyzed V6 region 16S rRNA gene sequences from 257 animal fecal samples and tested a subset of 184 using qPCR for human/sewage marker genes. Overall, specificities of human/sewage marker genes within sequencing data were 99.6% (BacV6-21), 96.9% (Lachno3), and 96.1% (HF183, indexed by its inferred V6 sequence). Occurrence of some true cross-reactions was associated with atypical compositions of organisms within the genera Blautia or Bacteroides For human/sewage marker qPCR assays, specificities were 96.7% (HF183/Bac287R), 96.2% (BacV6-21), 95.6% (human Bacteroides [HB]), and 94.0% (Lachno3). Select assays duplexed with either Escherichia coli or Enterococcus spp. were also validated. Most of the positive qPCR results in animals were low level and, on average, 2 orders of magnitude lower than the copy numbers of E. coli and Enterococcus spp. The lower specificity in qPCR assays compared to sequencing data was mainly caused by amplification of sequences highly similar to the marker gene and not the occurrence of the exact marker sequence in animal fecal samples.IMPORTANCE Identifying human sources of fecal pollution is critical to remediate sanitation concerns. Large financial investments are required to address these concerns; therefore, a high level of confidence in testing results is needed. Human fecal marker genes validated in this study showed high specificity in both sequencing data and qPCR results. Human marker sequences were rarely found in individual animals, and in most cases, the animals had atypical microbial communities. Sequencing also revealed the presence of closely related organisms that could account for nonspecific amplification in certain assays. Both the true cross-reactions and the nonspecific amplification had low signals well below E. coli or Enterococcus levels and likely would not impact the assay's ability to reliably detect human fecal pollution. No animal source had multiple human/sewage marker genes present; therefore, using a combination of marker genes would increase the confidence of human fecal pollution detection.

Computational analysis of the SARS-CoV-2 and other viruses based on the Kolmogorov's complexity and Shannon's information theories

This paper tackles the information of 133 RNA viruses available in public databases under the light of several mathematical and computational tools. First, the formal concepts of distance metrics, Kolmogorov complexity and Shannon information are recalled. Second, the computational tools available presently for tackling and visualizing patterns embedded in datasets, such as the hierarchical clustering and the multidimensional scaling, are discussed. The synergies of the common application of the mathematical and computational resources are then used for exploring the RNA data, cross-evaluating the normalized compression distance, entropy and Jensen-Shannon divergence, versus representations in two and three dimensions. The results of these different perspectives give extra light in what concerns the relations between the distinct RNA viruses.

Profiling Bacterial Diversity and Potential Pathogens in Wastewater Treatment Plants Using High-Throughput Sequencing Analysis

Next-generation sequencing provides new insights into the diversity and structure of bacterial communities, as well as the fate of pathogens in wastewater treatment systems. In this study, the bacterial community structure and the presence of pathogenic bacteria in three wastewater treatment plants across Gauteng province in South Africa were studied. The physicochemical results indicated that the quality of wastewater varies considerably from one plant to the others. Proteobacteria, Actinobacteria, Firmicutes, and Chloroflexi were the dominant phyla across the three wastewater treatment plants, while Alphaproteobacteria, Actinobacteria, Bacilli, and Clostridia were the dominant classes. The dominant bacterial functions were highly associated with carbohydrate, energy, and amino acid metabolism. In addition, potential pathogenic bacterial members identified from the influent/effluent samples included Roseomonas, Bacillus, Pseudomonas, Clostridium, Mycobacterium, Methylobacterium, and Aeromonas. The results of linear discriminant analysis (LDA) effect size analysis also confirmed that these bacterial pathogens were significantly abundant in the wastewater treatment systems. Further, the results of this study highlighted that the presence of bacterial pathogens in treated effluent pose a potential contamination risk, transmitted through soil, agriculture, water, or sediments. There is thus a need for continuous monitoring of potential pathogens in wastewater treatment plants (WWTPs) in order to minimize public health risk.

Ultraviolet disinfection impacts the microbial community composition and function of treated wastewater effluent and the receiving urban river

Background

In the United States, an estimated 14,748 wastewater treatment plants (WWTPs) provide wastewater collection, treatment, and disposal service to more than 230 million people. The quality of treated wastewater is often assessed by the presence or absence of fecal indicator bacteria. UV disinfection of wastewater is a common final treatment step used by many wastewater treatment plants in order to reduce fecal coliform bacteria and other pathogens; however, its potential impacts on the total effluent bacterial community are seemingly varied. This is especially important given that urban WWTPs typically return treated effluent to coastal and riverine environments and thus are a major source of microorganisms, genes, and chemical compounds to these systems. Following rainfall, stormflow conditions can result in substantial increases to effluent flow into combined systems.

Methods

Here, we conducted a lab-scale UV disinfection on WWTP effluent using UV dosage of 100 mJ/cm² and monitored the active microbiome in UV-treated effluent and untreated effluent over the course of 48 h post-exposure using 16S rRNA sequencing. In addition, we simulated stormflow conditions with effluent UV-treated and untreated effluent additions to river water and compared the microbial communities to those in baseflow river water. We also tracked the functional profiles of genes involved in tetracycline resistance (tetW) and nitrification (amoA) in these microcosms using RT-qPCR.

Results

We showed that while some organisms, such as members of the Bacteroidetes, are inhibited by UV disinfection and overall diversity of the microbial community decreases following treatment, many organisms not only survive, but remain active. These include common WWTP-derived organisms such as Comamonadaceae and Pseudomonas. When combined with river water to mimic stormflow conditions, these organisms can persist in the environment and potentially enhance microbial functions such as nitrification and antibiotic resistance.

Role of antibiotic use, plasma citrulline and blood microbiome in advanced non-small cell lung cancer patients treated with nivolumab

BACKGROUND

Recent data suggested a role of gut microbiota and antibiotic use on immune checkpoint inhibitors efficacy. We aimed to evaluate the impact of early use of antibiotic (EUA), blood microbiome and plasmatic citrulline (marker of the intestinal barrier) on nivolumab efficacy in non-small cell lung cancer (NSCLC).

METHODS

We included all consecutive patients with advanced NSCLC treated with nivolumab in our Department between 2014 and 2017. Blood microbiome was analyzed at month (M) M0 and M2. Citrulline rates were evaluated at M0, M2, M4 and M6.

RESULTS

Seventy-two patients were included (EUA in 42%). Overall survival (OS) was longer without EUA (median 13.4 months) than with EUA (5.1 months, p = 0.03). Thirty-five patients (49%) had plasma samples available. High citrulline rate (≥20 μM) at M0 was associated with tumor response (p = 0.084) and clinical benefit (nivolumab > 6 months) (p = 0.002). Median progression-free survival (PFS) was 7.9 months (high citrulline) vs 1.6 months (low citrulline) (p < 0.0001), and median OS were respectively non reached vs 2.2 months (p < 0.0001). Patients with EUA had lower median citrulline rates at M0: 21 μM (IQR 15.0-30.8) vs 32 μM (IQR 24.0-42.0) without EUA (p = 0.044). The presence of specific bacterial DNA in blood at M0 was associated with response and clinical benefit (Peptostreptococcae, Paludibaculum, Lewinella) or with tumor progression (Gemmatimonadaceae). Multivariate analyses on PFS and OS confirmed the prognostic role of citrulline and blood microbiome.

CONCLUSIONS

EUA is associated with shorter OS with nivolumab and lower citrulline rates. Plasma citrulline and blood microbiome appear to be promising predictive factors of nivolumab efficacy.

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.

Effect of Long-Term Farming Practices on Agricultural Soil Microbiome Members Represented by Metagenomically Assembled Genomes (MAGs) and Their Predicted Plant-Beneficial Genes

To follow the hypothesis that agricultural management practices affect structure and function of the soil microbiome regarding soil health and plant-beneficial traits, high-throughput (HT) metagenome analyses were performed on Chernozem soil samples from a long-term field experiment designated LTE-1 carried out at Bernburg-Strenzfeld (Saxony-Anhalt, Germany). Metagenomic DNA was extracted from soil samples representing the following treatments: (i) plough tillage with standard nitrogen fertilization and use of fungicides and growth regulators, (ii) plough tillage with reduced nitrogen fertilization (50%), (iii) cultivator tillage with standard nitrogen fertilization and use of fungicides and growth regulators, and (iv) cultivator tillage with reduced nitrogen fertilization (50%). Bulk soil (BS), as well as root-affected soil (RS), were considered for all treatments in replicates. HT-sequencing of metagenomic DNA yielded approx. 100 Giga bases (Gb) of sequence information. Taxonomic profiling of soil communities revealed the presence of 70 phyla, whereby Proteobacteria, Actinobacteria, Bacteroidetes, Planctomycetes, Acidobacteria, Thaumarchaeota, Firmicutes, Verrucomicrobia and Chloroflexi feature abundances of more than 1%. Functional microbiome profiling uncovered, i.a., numerous potential plant-beneficial, plant-growth-promoting and biocontrol traits predicted to be involved in nutrient provision, phytohormone synthesis, antagonism against pathogens and signal molecule synthesis relevant in microbe-plant interaction. Neither taxonomic nor functional microbiome profiling based on single-read analyses revealed pronounced differences regarding the farming practices applied. Soil metagenome sequences were assembled and taxonomically binned. The ten most reliable and abundant Metagenomically Assembled Genomes (MAGs) were taxonomically classified and metabolically reconstructed. Importance of the phylum Thaumarchaeota for the analyzed microbiome is corroborated by the fact that the four corresponding MAGs were predicted to oxidize ammonia (nitrification), thus contributing to the cycling of nitrogen, and in addition are most probably able to fix carbon dioxide. Moreover, Thaumarchaeota and several bacterial MAGs also possess genes with predicted functions in plant-growth-promotion. Abundances of certain MAGs (species resolution level) responded to the tillage practice, whereas the factors compartment (BS vs. RS) and nitrogen fertilization only marginally shaped MAG abundance profiles. Hence, soil management regimes promoting plant-beneficial microbiome members are very likely advantageous for the respective agrosystem, its health and carbon sequestration and accordingly may enhance plant productivity. Since Chernozem soils are highly fertile, corresponding microbiome data represent a valuable reference resource for agronomy in general.

Single Core Genome Sequencing for Detection of both Borrelia burgdorferi Sensu Lato and Relapsing Fever Borrelia Species

Lyme disease, initially described as Lyme arthritis, was reported before nucleic-acid based detection technologies were available. The most widely used diagnostic tests for Lyme disease are based on the serologic detection of antibodies produced against antigens derived from a single strain of Borrelia burgdorferi. The poor diagnostic accuracy of serological tests early in the infection process has been noted most recently in the 2018 Report to Congress issued by the U.S. Department of Health and Human Services Tick-Borne Disease Working Group. Clinical Lyme disease may be caused by a diversity of borreliae, including those classified as relapsing fever species, in the United States and in Europe. It is widely accepted that antibiotic treatment of Lyme disease is most successful during this critical early stage of infection. While genomic sequencing is recognized as an irrefutable direct detection method for laboratory diagnosis of Lyme borreliosis, development of a molecular diagnostic tool for all clinical forms of borreliosis is challenging because a “core genome” shared by all pathogenic borreliae has not yet been identified. After a diligent search of the GenBank database, we identified two highly conserved segments of DNA sequence among the borrelial 16S rRNA genes. We further developed a pair of Borrelia genus-specific PCR primers for amplification of a segment of borrelial 16S rRNA gene as a “core genome” to be used as the template for routine Sanger sequencing-based metagenomic direct detection test. This study presented examples of base-calling DNA sequencing electropherograms routinely generated in a clinical diagnostic laboratory on DNA extracts of human blood specimens and ticks collected from human skin bites and from the environment. Since some of the tick samples tested were collected in Ireland, borrelial species or strains not known to exist in the United States were also detected by analysis of this 16S rRNA “core genome”. We recommend that hospital laboratories located in Lyme disease endemic areas begin to use a “core genome” sequencing test to routinely diagnose spirochetemia caused by various species of borreliae for timely management of patients at the early stage of infection.

Distinct gut microbiota profile in antiretroviral therapy-treated perinatally HIV-infected patients associated with cardiac and inflammatory biomarkers

OBJECTIVE

Persistent inflammation and higher risk to develop cardiovascular diseases still represent a major complication for HIV-infected patients despite effective antiretroviral therapy (ART). We investigated the correlation between the gut microbiota profile, markers of inflammation, vascular endothelial activation (VEA) and microbial translocation (MT) in perinatally HIV-infected patients (PHIV) under ART.

DESIGN

Cross-sectional study including 61 ART-treated PHIV (age range 3-30 years old) and 71 age-matched healthy controls. Blood and stool sample were collected at the same time and analyzed for gut microbiota composition and plasma biomarkers.

METHODS

Gut microbiota composition was determined by 16S rRNA targeted-metagenomics. Soluble markers of MT, inflammation and VEA were quantified by ELISA or Luminex assay. Markers of immune activation were analyzed by flow cytometry on CD4 and CD8T cells.

RESULTS

We identified two distinct gut microbiota profiles (groups A and B) among PHIV. No different clinical parameters (age, sex, ethnicity, clinical class), dietary and sexual habits were found between the groups. The group A showed a relative dominance of Akkermansia muciniphila, whereas gut microbiota of group B was characterized by a higher biodiversity. The analysis of soluble markers revealed a significantly higher level of soluble E-selectine (P = 0.0296), intercellular adhesion molecule-1 (P = 0.0028), vascular adhesion molecule-1 (P = 0.0230), IL-6 (P = 0.0247) and soluble CD14 (P = 0.0142) in group A compared with group B.

CONCLUSION

Distinctive gut microbiota profiles are differently associated with inflammation, microbial translocation and VEA. Future studies are needed to understand the role of A. muciniphila and risk to develop cardiovascular diseases in PHIV.

Endophytic Bacterial Communities Associated with Roots and Leaves of Plants Growing in Chilean Extreme Environments

Several studies have demonstrated the relevance of endophytic bacteria on the growth and fitness of agriculturally-relevant plants. To our knowledge, however, little information is available on the composition, diversity, and interaction of endophytic bacterial communities in plants struggling for existence in the extreme environments of Chile, such as the Atacama Desert (AD) and Patagonia (PAT). The main objective of the present study was to analyze and compare the composition of endophytic bacterial communities associated with roots and leaves of representative plants growing in Chilean extreme environments. The plants sampled were: Distichlis spicate and Pluchea absinthioides from the AD, and Gaultheria mucronata and Hieracium pilosella from PAT. The abundance and composition of their endophytic bacterial communities was determined by quantitative PCR and high–throughput sequencing of 16S rRNA, respectively. Results indicated that there was a greater abundance of 16S rRNA genes in plants from PAT (10¹³ to 10¹⁴ copies g⁻¹ DNA), compared with those from AD (10¹⁰ to 10¹² copies g⁻¹ DNA). In the AD, a greater bacterial diversity, as estimated by Shannon index, was found in P. absinthioides, compared with D. spicata. In both ecosystems, the greater relative abundances of endophytes were mainly attributed to members of the phyla Proteobacteria (14% to 68%), Firmicutes (26% to 41%), Actinobacteria (6 to 23%) and Bacteroidetes (1% to 21%). Our observations revealed that most of operational taxonomic units (OTUs) were not shared between tissue samples of different plant species in both locations, suggesting the effect of the plant genotype (species) on the bacterial endophyte communities in Chilean extreme environments, where Bacillaceae and Enterobacteriacea could serve as keystone taxa as revealed our linear discriminant analysis.

MNEMONIC: MetageNomic Experiment Mining to create an OTU Network of Inhabitant Correlations

Background

The number of publicly available metagenomic experiments in various environments has been rapidly growing, empowering the potential to identify similar shifts in species abundance between different experiments. This could be a potentially powerful way to interpret new experiments, by identifying common themes and causes behind changes in species abundance.

Results

We propose a novel framework for comparing microbial shifts between conditions. Using data from one of the largest human metagenome projects to date, the American Gut Project (AGP), we obtain differential abundance vectors for microbes using experimental condition information provided with the AGP metadata, such as patient age, dietary habits, or health status. We show it can be used to identify similar and opposing shifts in microbial species, and infer putative interactions between microbes. Our results show that groups of shifts with similar effects on microbiome can be identified and that similar dietary interventions display similar microbial abundance shifts.

Conclusions

Without comparison to prior data, it is difficult for experimentalists to know if their observed changes in species abundance have been observed by others, both in their conditions and in others they would never consider comparable. Yet, this can be a very important contextual factor in interpreting the significance of a shift. We’ve proposed and tested an algorithmic solution to this problem, which also allows for comparing the metagenomic signature shifts between conditions in the existing body of data.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2623-x) contains supplementary material, which is available to authorized users.

Protective effect of Bacillus amyloliquefaciens against Salmonella via polarizing macrophages to M1 phenotype directly and to M2 depended on microbiota

Bacillus amyloliquefaciens SC06 (BaSC06), a potential probiotic, plays a positive role in animal growth performance and immune function.

Predicting recurrence of Clostridium difficile infection following encapsulated fecal microbiota transplantation

BACKGROUND

Fecal microbiota transplantation (FMT) is an effective treatment for recurrent Clostridium difficile infection (rCDI). The use of freeze-dried, encapsulated donor material for FMT (cap-FMT) allows for an easy route of administration and remains clinically effective in the majority of rCDI patients. We hypothesized that specific shifts in the microbiota in response to cap-FMT could predict clinical outcome. We further evaluated the degree of donor microbiota engraftment to determine the extent that donor transfer contributed to recovery.

RESULTS

In total, 89 patients were treated with 100 separate cap-FMTs, with a success rate (no rCDI 60 days post cap-FMT) of 80%. Among responders, the lower alpha diversity (ANOVA P < 0.05) observed among patient's pre-FMT samples was restored following cap-FMT. At 1 week post-FMT, community composition varied by clinical outcome (ANOSIM P < 0.001), with similar abundances among families (Lachnospiraceae, Ruminococcaceae, and Bacteroidaceae) in responder and donor samples. Families that showed differential abundances by outcome (response vs. recurrence) from samples collected 7 days following cap-FMT were used to construct a regression tree-based model to predict recurrence. Results showed a training accuracy of 100% to predict recurrence and the model was 97% accurate against a test data set of samples collected 8-20 days following cap-FMT. Evaluation of the extent of engraftment using the Bayesian algorithm SourceTracker revealed that approximately 50% of the post-FMT communities of responders were attributable to donor microbiota, while an additional 20-30% of the communities were similar to a composite healthy microbiota consisting of all donor samples.

CONCLUSIONS

Regression tree-based analyses of microbial communities identified taxa significantly related to clinical response after 7 days, which can be targeted to improve microbial therapeutics. Furthermore, reinstatement of a healthy assemblage following cap-FMT was only partially attributable to explicit donor engraftment and continued to develop towards an overall healthy assemblage, independent of donor.

Characterizing oral microbial communities across dentition states and colonization niches

METHODS

The present study aimed to identify patterns and processes in acquisition of oral bacteria and to characterize the microbiota of different dentition states and habitats. Mucosal, salivary, supragingival, and subgingival biofilm samples were collected from orally and systemically healthy children and mother-child dyads in predentate, primary, mixed, and permanent dentitions. 16S rRNA gene sequences were compared to the Human Oral Microbiome Database (HOMD). Functional potential was inferred using PICRUSt.

RESULTS

Unweighted and weighted UniFrac distances were significantly smaller between each mother-predentate dyad than infant-unrelated female dyads. Predentate children shared a median of 85% of species-level operational taxonomic units (s-OTUs) and 100% of core s-OTUs with their mothers. Maternal smoking, but not gender, mode of delivery, feeding habits, or type of food discriminated between predentate microbial profiles. The primary dentition demonstrated expanded community membership, structure, and function when compared to the predentate stage, as well as significantly lower similarity between mother-child dyads. The primary dentition also included 85% of predentate core s-OTUs. Subsequent dentitions exhibited over 90% similarity to the primary dentition in phylogenetic and functional structure. Species from the predentate mucosa as well as new microbial assemblages were identified in the primary supragingival and subgingival microbiomes. All individuals shared 65% of species between supragingival and subgingival habitats; however, the salivary microbiome exhibited less than 35% similarity to either habitat.

CONCLUSIONS

Within the limitations of a cross-sectional study design, we identified two definitive stages in oral bacterial colonization: an early predentate imprinting and a second wave with the eruption of primary teeth. Bacterial acquisition in the oral microbiome is influenced by the maternal microbiome. Personalization begins with the eruption of primary teeth; however, this is limited to phylogeny; functionally, individuals exhibit few differences, suggesting that microbial assembly may follow a defined schematic that is driven by the functional requirements of the ecosystem. This early microbiome forms the foundation upon which newer communities develop as more colonization niches emerge, and expansion of biodiversity is attributable to both introduction of new species and increase in abundance of predentate organisms.

Urea Amendment Decreases Microbial Diversity and Selects for Specific Nitrifying Strains in Eight Contrasting Agricultural Soils

Application of nitrogen (N) fertilizers, predominantly as urea, is a major source of reactive N in the environment, with wide ranging effects including increased greenhouse gas accumulation in the atmosphere and aquatic eutrophication. The soil microbial community is the principal driver of soil N cycling; thus, improved understanding of microbial community responses to urea addition has widespread implications. We used next-generation amplicon sequencing of the 16S rRNA gene to characterize bacterial and archaeal communities in eight contrasting agricultural soil types amended with 0, 100, or 500 μg N g^-1 of urea and incubated for 21 days. We hypothesized that urea amendment would have common, direct effects on the abundance and diversity of members of the microbial community associated with nitrification, across all soils, and would further affect the broader heterotrophic community resulting in decreased diversity and variation in abundances of specific taxa. Significant (P < 0.001) differences in bacterial community diversity and composition were observed by site, but amendment with only the greatest urea concentration significantly decreased Shannon indices. Expansion in the abundances of members of the families Microbacteriaceae, Chitinophagaceae, Comamonadaceae, Xanthomonadaceae, and Nitrosomonadaceae were also consistently observed among all soils (linear discriminant analysis score ≥ 3.0). Analysis of nitrifier genera revealed diverse, soil-specific distributions of oligotypes (strains), but few were correlated with nitrification gene abundances that were reported in a previous study. Our results suggest that the majority of the bacterial and archaeal community are likely unassociated with N cycling, but are significantly negatively impacted by urea application. Furthermore, these results reveal that amendment with high concentrations of urea may reduce nitrifier diversity, favoring specific strains, specifically those within the nitrifying genera Nitrobacter, Nitrospira, and Nitrosospira, that may play significant roles related to N cycling in soils receiving intensive urea inputs.

Application of SourceTracker for Accurate Identification of Fecal Pollution in Recreational Freshwater: A Double-Blinded Study

The efficacy of SourceTracker software to attribute contamination from a variety of fecal sources spiked into ambient freshwater samples was investigated. Double-blinded samples spiked with ≤5 different sources (0.025-10% vol/vol) were evaluated against fecal taxon libraries characterized by next-generation amplicon sequencing. Three libraries, including an initial library (17 nonlocal sources), a blinded source library (5 local sources), and a composite library (local and nonlocal sources), were used with SourceTracker. SourceTracker's predictions of fecal compositions in samples were made, in part, based on distributions of taxa within abundant genera identified as discriminatory by discriminant analyses but also using a large percentage of low abundance taxa. The initial library showed poor ability to characterize blinded samples, but, using local sources, SourceTracker showed 91% accuracy (31/34) at identifying the presence of source contamination, with two false positives for sewage and one for horse. Furthermore, sink predictions of source contamination were positively correlated (Spearman's ρ ≥ 0.88, P < 0.001) with spiked source volumes. Using the composite library did not significantly affect sink predictions ( P > 0.79) compared to those made using the local sources alone. Results of this study indicate that geographically associated fecal samples are required for SourceTracker to assign host sources accurately.

Predicting the Functional Potential of the Microbiome from Marker Genes Using PICRUSt

Marker-gene sequencing is a cost-effective method of taxonomically profiling microbial communities. Unlike metagenomic approaches, marker-gene sequencing does not provide direct information about the functional genes that are present in the genomes of community members. However, by capitalizing on the rapid growth in the number of sequenced genomes, it is possible to infer which functions are likely associated with a marker gene based on its sequence similarity with a reference genome. The PICRUSt tool is based on this idea and can predict functional category abundances based on an input marker gene. In brief, this method requires a reference phylogeny with tips corresponding to taxa with reference genomes as well as taxa lacking sequenced genomes. A modified ancestral state reconstruction (ASR) method is then used to infer counts of functional categories for taxa without reference genomes. The predictions are written to pre-calculated files, which can be cross-referenced with other datasets to quickly generate predictions of functional potential for a community. This chapter will give an in-depth description of these methods and describe how PICRUSt should be used.