The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses

Microbiota profiling in esophageal diseases: Novel insights into molecular staining and clinical outcomes

Gut microbiota is recognized nowadays as one of the key players in the development of several gastro-intestinal diseases. The first studies focused mainly on healthy subjects with staining of main bacterial species via culture-based techniques. Subsequently, lots of studies tried to focus on principal esophageal disease enlarged the knowledge on esophageal microbial environment and its role in pathogenesis. Gastro Esophageal Reflux Disease (GERD), the most widespread esophageal condition, seems related to a certain degree of mucosal inflammation, via interleukin (IL) 8 potentially enhanced by bacterial components, lipopolysaccharide (LPS) above all. Gram- bacteria, producing LPS), such as Campylobacter genus, have been found associated with GERD. Barrett esophagus (BE) seems characterized by a Gram- and microaerophils-shaped microbiota. Esophageal cancer (EC) development leads to an overturn in the esophageal environment with the shift from an oral-like microbiome to a prevalently low-abundant and low-diverse Gram--shaped microbiome. Although underinvestigated, also changes in the esophageal microbiome are associated with rare chronic inflammatory or neuropathic disease pathogenesis. The paucity of knowledge about the microbiota-driven mechanisms in esophageal disease pathogenesis is mainly due to the scarce sensitivity of sequencing technology and culture methods applied so far to study commensals in the esophagus. However, the recent advances in molecular techniques, especially with the advent of non-culture-based genomic sequencing tools and the implementation of multi-omics approaches, have revolutionized the microbiome field, with promises of implementing the current knowledge, discovering more mechanisms underneath, and giving insights into the development of novel therapies aimed to re-establish the microbial equilibrium for ameliorating esophageal diseases..

Identification of microbial communities and multi-species biofilms contamination in seafood processing environments with different hygiene conditions

Biofilms formed by spoilage and pathogenic bacteria increase microbial persistence, causing an adverse influence on the quality of seafood. The mono-species biofilms are widely reported, however, the contamination of multi-species biofilms and their matrix in food environments are still not fully understood. Here, we assessed the contamination of multi-species biofilms in three seafood processing environments with different hygiene levels by detecting bacterial number and three biofilm matrix components (carbohydrates, extracellular DNA (eDNA), and proteins). Samples comprising seven food matrix surfaces and eight food processing equipment surfaces were collected from two seafood processing plants (XY and XC) and one seafood market (CC). The results showed that the bacterial counts ranged from 1.89 to 4.91 CFU/cm2 and 5.68 to 9.15 BCE/cm2 in these surfaces by cultivation and real-time PCR, respectively. Six biofilm hotspots were identified, including four in CC and two in XY. Among the three processing environments, the amplicon sequence variants (ASVs) of Proteobacteria, Bacteroidetes, and Actinobacteria decreased with improved processing hygiene, while Firmicutes showed a decrease in the four most abundant phyla. The most prevalent bacteria belonged to genera Psychrobacter, Acinetobacter, and Pseudomonas, demonstrating the significant differences and alteration in bacterial community composition during different environments. From the biofilm hotspots, 15 isolates with strong biofilm forming ability were identified, including 7 Pseudomonas, 7 Acinetobacter, and 1 Psychrobacter. The Pseudomonas isolates exhibited the highest production of EPS components and three strong motilities, whose characteristics were positively correlated. Thus, this study verified the presence of multi-species biofilms in seafood processing environments, offering preliminary insights into the diversity of microbial communities during processing. It highlights potential contamination sources and emphasizes the importance of understanding biofilms composition to control biofilms formation in seafood processing environments.

An ultrasensitive genosensor for detection of toxigenic and non-toxigenic Clostridioides difficile based on a conserved sequence in surface layer protein coding gene

Clostridioides difficile (C. difficile) is the most common agent of antibiotic-associated diarrhea, leading to intestinal infection through the secretion of two major toxins. Not all strains of this bacterium are toxigenic, but some of them cause infection via their accessory virulence factors, such as surface layer protein (SlpA). SlpA is conserved in both toxigenic and non-toxigenic strains of C. difficile. In the present work, an amplification-free electrochemical genosensor was designed for the detection of the slpA gene. A glassy carbon electrode coated with gold nanoparticle-reduced graphene oxide nanocomposite was used as the working electrode, and its surface was modified using a simple thiolated linear oligonucleotide as the bioreceptor. Moreover, the hexaferrocenium tri[hexa(isothiocyanato) iron(III)] trihydroxonium (HxFc) complex was used as an intercalator, and its redox signal was recorded using differential pulse voltammetry. Scan rate studies indicated a quasi-reversible adsorption-controlled process for the HxFc complex. This genosensor showed high sensitivity with a limit of detection of 0.2 fM, a linear response range of 0.46-1900 fM, and a satisfactory specificity toward the synthetic slpA target gene. Also, the genosensor indicated responses in the mentioned linear range toward the genome extracted from either toxigenic or non-toxigenic strains of C. difficile.

Analysis of the Diversity and Functional Potential of Bacterial Communities in Tuberculomas

The dynamics of lung microbiota in tuberculosis remains poorly understood. Sequencing of variable regions of the 16S rRNA gene from surgically excised tuberculosis foci and biopsy specimens of normal lung tissue allowed characterization of the diversity and predictive potential of bacterial communities. Taxonomic diversity indices attested to differences in the structure of microbial communities between "healthy" lungs and tuberculomas. The microbial composition of "healthy" lungs varied in taxonomic diversity and was presented by both gram-positive and gram-negative bacteria with sufficiently similar metabolic potential. The microbiota of the examined tuberculomas consisted of Mycobacterium tuberculosis in 99.9% of cases. A significant part of the metabolic pathways predicted by PICRUSt2 included cholesterol catabolism, sulfate assimilation, and various pathways for the biosynthesis of cell wall components.

Revisiting Wolbachia detections: Old and new issues in Aedes aegypti mosquitoes and other insects

Wolbachia continue to be reported in species previously thought to lack them, particularly Aedes aegypti mosquitoes. The presence of Wolbachia in this arbovirus vector is considered important because releases of mosquitoes with transinfected Wolbachia are being used around the world to suppress pathogen transmission and these efforts depend on a lack of Wolbachia in natural populations of this species. We previously assessed papers reporting Wolbachia in natural populations of Ae. aegypti and found little evidence that seemed convincing. However, since our review, more and more papers are emerging on Wolbachia detections in this species. Our purpose here is to evaluate these papers within the context of criteria we previously established but also new criteria that include the absence of releases of transinfections within the local areas being sampled which has contaminated natural populations in at least one case where novel detections have been reported. We also address the broader issue of Wolbachia detection in other insects where similar issues may arise which can affect overall estimates of this endosymbiont more generally. We note continuing shortcomings in papers purporting to find natural Wolbachia in Ae. aegypti which are applicable to other insects as well.

Influence of empirically derived filtering parameters, ASV, and OTU pipelines on assessing rumen microbial diversity

Microbes play an important role in human and animal health as well as animal productivity. The host microbial interactions within ruminants play a critical role in animal health and productivity and provide up to 70% of the animal's energy need in the form of fermentation products. As such, many studies have investigated microbial community composition to understand microbial community changes and factors that affect microbial colonization and persistence. The advances in next generation sequencing (NGS) technologies and low cost of sequencing have gravitated many studies to utilize 16S rDNA-based analysis tools for interrogation of microbiomes at a much finer scale than traditional culturing. However, such methods that rely on single base pair differences for bacterial taxa clustering may inflate or underestimate diversity leading to inaccurate identification of bacterial diversity. Therefore, in this study, we sequenced mock communities of known membership and abundance to establish filtration parameters to reduce inflation of microbial diversity due to PCR and sequencing errors. Additionally, we evaluated the effect of the resulting filtering parameters proposed using established bioinformatic pipelines on a study consisting of Holstein and Jersey cattle to identify bread and treatment effects on the bacterial community composition and the impact of the filtering on global microbial community structure analysis and results. Filtration resulted in a sharp reduction in bacterial taxa identified, yet retain most sequencing data (retaining > 79% of sequencing reads) when analyzed using 3 different microbial analysis pipelines (DADA2, Mothur, USEARCH). After filtration, conclusions from α and β-diversity tests show very similar results across all analysis methods. The mock community-based filtering parameters proposed in this study help provide a more realistic estimation of bacterial diversity. Additionally, the filtration reduced the variation between microbiome analysis methods and help identify microbial community differences that could have been missed due to large animal to animal variation observed in the unfiltered data. As such, we believe, the new filtering parameters described in this study will help obtain diversity estimates closer to realistic values and will improve the ability of detecting microbial community differences and help better understand microbial community changes in 16S rDNA-based studies.

Augmenting bacterial similarity measures using a graph-based genome representation

Relationships between bacterial taxa are traditionally defined using 16S rRNA nucleotide similarity or average nucleotide identity. Improvements in sequencing technology provide additional pairwise information on genome sequences, which may provide valuable information on genomic relationships. Mapping orthologous gene locations between genome pairs, known as synteny, is typically implemented in the discovery of new species and has not been systematically applied to bacterial genomes. Using a data set of 378 bacterial genomes, we developed and tested a new measure of synteny similarity between a pair of genomes, which was scaled onto 16S rRNA distance using covariance matrices. Based on the input gene functions used (i.e., core, antibiotic resistance, and virulence), we observed varying topological arrangements of bacterial relationship networks by applying (i) complete linkage hierarchical clustering and (ii) K-nearest neighbor graph structures to synteny-scaled 16S data. Our metric improved clustering quality comparatively to state-of-the-art average nucleotide identity metrics while preserving clustering assignments for the highest similarity relationships. Our findings indicate that syntenic relationships provide more granular and interpretable relationships for within-genera taxa compared to pairwise similarity measures, particularly in functional contexts.

IMPORTANCE

Given the prevalence and necessity of the 16S rRNA measure in bacterial identification and analysis, this additional analysis adds a functional and synteny-based layer to the identification of relatives and clustering of bacteria genomes. It is also of computational interest to model the bacterial genome as a graph structure, which presents new avenues of genomic analysis for bacteria and their closely related strains and species.

Preliminary profile of the gut microbiota from amerindians in the Brazilian amazon experiencing a process of transition to urbanization

The Yanomami are one of the oldest indigenous tribes in the Amazon and are direct descendants of the first people to colonize South America 12,000 years ago. They are located on the border between Venezuela and Brazil, with the Venezuelan side remaining uncontacted. While they maintain a hunter-gatherer society, they are currently experiencing contact with urbanized populations in Brazil. The human gut microbiota of traditional communities has become the subject of recent studies due to the Westernization of their diet and the introduction of antibiotics and other chemicals, which have affected microbial diversity in indigenous populations, thereby threatening their existence. In this study, we preliminarily characterized the diversity of the gut microbiota of the Yanomami, a hunter-gatherer society from the Amazon, experiencing contact with urbanized populations. Similarly, we compared their diversity with the population in Manaus, Amazonas. A metabarcoding approach of the 16 S rRNA gene was carried out on fecal samples. Differences were found between the two populations, particularly regarding the abundance of genera (e.g., Prevotella and Bacteroides) and the higher values of the phyla Bacteroidetes over Firmicutes, which were significant only in the Yanomami. Some bacteria were found exclusively in the Yanomami (Treponema and Succinivibrio). However, diversity was statistically equal between them. In conclusion, the composition of the Yanomami gut microbiota still maintains the profile characteristic of a community with a traditional lifestyle. However, our results suggest an underlying Westernization process of the Yanomami microbiota when compared with that of Manaus, which must be carefully monitored by authorities, as the loss of diversity can be a sign of growing danger to the health of the Yanomami.

Determining the footprint of breeding in the seed microbiome of a perennial cereal

BACKGROUND

Seed endophytes have a significant impact on plant health and fitness. They can be inherited and passed on to the next plant generation. However, the impact of breeding on their composition in seeds is less understood. Here, we studied the indigenous seed microbiome of a recently domesticated perennial grain crop (Intermediate wheatgrass, Thinopyrum intermedium L.) that promises great potential for harnessing microorganisms to enhance crop performance by a multiphasic approach, including amplicon and strain libraries, as well as molecular and physiological assays.

RESULTS

Intermediate wheatgrass seeds harvested from four field sites in Europe over three consecutive years were dominated by Proteobacteria (88%), followed by Firmicutes (10%). Pantoea was the most abundant genus and Pantoea agglomerans was identified as the only core taxon present in all samples. While bacterial diversity and species richness were similar across all accessions, the relative abundance varied especially in terms of low abundant and rare taxa. Seeds from four different breeding cycles (TLI C3, C5, C704, C801) showed significant differences in bacterial community composition and abundance. We found a decrease in the relative abundance of the functional genes nirK and nifH as well as a drop in bacterial diversity and richness. This was associated with a loss of amplicon sequence variants (ASVs) in Actinobacteria, Alphaproteobacteria, and Bacilli, which could be partially compensated in offspring seeds, which have been cultivated at a new site. Interestingly, only a subset assigned to potentially beneficial bacteria, e.g. Pantoea, Kosakonia, and Pseudomonas, was transmitted to the next plant generation or shared with offspring seeds.

CONCLUSION

Overall, this study advances our understanding of the assembly and transmission of endophytic seed microorganisms in perennial intermediate wheatgrass and highlights the importance of considering the plant microbiome in future breeding programs.

Utilizing novel Escherichia coli-specific conserved signature proteins for enhanced monitoring of recreational water quality

Escherichia coli serves as a proxy indicator of fecal contamination in aquatic ecosystems. However, its identification using traditional culturing methods can take up to 24 h. The application of DNA markers, such as conserved signature proteins (CSPs) genes (unique to all species/strains of a specific taxon), can form the foundation for novel polymerase chain reaction (PCR) tests that unambiguously identify and detect targeted bacterial taxa of interest. This paper reports the identification of three new highly-conserved CSPs (genes), namely YahL, YdjO, and YjfZ, which are exclusive to E. coli/Shigella. Using PCR primers based on highly conserved regions within these CSPs, we have developed quantitative PCR (qPCR) assays for the evaluation of E. coli/Shigella species in water ecosystems. Both in-silico and experimental PCR testing confirmed the absence of sequence match when tested against other bacteria, thereby confirming 100% specificity of the tested CSPs for E. coli/Shigella. The qPCR assays for each of the three CSPs provided reliable quantification for all tested enterohaemorrhagic and environmental E. coli strains, a requirement for water testing. For recreational water samples, CSP-based quantification showed a high correlation (r > 7, p < 0.01) with conventional viable E. coli enumeration. This indicates that novel CSP-based qPCR assays for E. coli can serve as robust tools for monitoring water ecosystems and other critical areas, including food monitoring.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Endometrial Cancer: A Pilot Study of the Tissue Microbiota

BACKGROUND

The endometrium remains a difficult tissue for the analysis of microbiota, mainly due to the low bacterial presence and the sampling procedures. Among its pathologies, endometrial cancer has not yet been completely investigated for its relationship with microbiota composition. In this work, we report on possible correlations between endometrial microbiota dysbiosis and endometrial cancer.

METHODS

Women with endometrial cancer at various stages of tumor progression were enrolled together with women with a benign polymyomatous uterus as the control. Analyses were performed using biopsies collected at two specific endometrial sites during the surgery. This study adopted two approaches: the absolute quantification of the bacterial load, using droplet digital PCR (ddPCR), and the analysis of the bacterial composition, using a deep metabarcoding NGS procedure.

RESULTS

ddPCR provided the first-ever assessment of the absolute quantification of bacterial DNA in the endometrium, confirming a generally low microbial abundance. Metabarcoding analysis revealed a different microbiota distribution in the two endometrial sites, regardless of pathology, accompanied by an overall higher prevalence of pathogenic bacterial genera in cancerous tissues.

CONCLUSIONS

These results pave the way for future studies aimed at identifying potential biomarkers and gaining a deeper understanding of the role of bacteria associated with tumors.

Research progress in isolation and identification of rumen probiotics

With the increasing research on the exploitation of rumen microbial resources, rumen probiotics have attracted much attention for their positive contributions in promoting nutrient digestion, inhibiting pathogenic bacteria, and improving production performance. In the past two decades, macrogenomics has provided a rich source of new-generation probiotic candidates, but most of these "dark substances" have not been successfully cultured due to the restrictive growth conditions. However, fueled by high-throughput culture and sorting technologies, it is expected that the potential probiotics in the rumen can be exploited on a large scale, and their potential applications in medicine and agriculture can be explored. In this paper, we review and summarize the classical techniques for isolation and identification of rumen probiotics, introduce the development of droplet-based high-throughput cell culture and single-cell sequencing for microbial culture and identification, and finally introduce promising cultureomics techniques. The aim is to provide technical references for the development of related technologies and microbiological research to promote the further development of the field of rumen microbiology research.

Rhodoferax potami sp. nov. and Rhodoferax mekongensis sp. nov., isolated from the Mekong River in Thailand

Four newly discovered Gram-stain-negative bacteria, designated as BL00010T, BL00058, D8-11T and BL00200, were isolated from water samples collected at three hydrological monitoring stations (namely Chiang Saen, Chiang Khan and Nong Khai) located along the Mekong River in Thailand. An investigation encompassing phenotypic, chemotaxonomic and genomic traits was conducted. The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that all four isolates represented members of the genus Rhodoferax. These isolates were closely related to Rhodoferax bucti KCTC 62564T with a similarity of 99.59%. The major fatty acids of the four novel isolates included C16:0 and C16:1ω7c and/or C16 : 1ω6c, whereas the major respiratory quinone was identified as ubiquinone Q-8. In addition, phosphatidylethanolamine was identified as a major polar lipid in these bacteria. The genomes of BL00010T, BL00058, D8-11T and BL00200 were similar in size (3.88-4.01 Mbp) and DNA G+C contents (59.5, 59.3, 59.5 and 59.3 mol%, respectively). In contrast to R. bucti KCTC 62564T and Rhodoferax aquaticus KCTC 32394T, the newly discovered species possessed several genes involved in nitrite and nitrile metabolism, which may be related to their unique adaptation to nitrile-rich environments. From the results of the pairwise analysis of average nucleotide identity of the whole genome and digital DNA-DNA hybridisation, it was evident that BL00010T and D8-11T represented two novel species, for which we propose the nomenclature Rhodoferax potami sp. nov., with the type strain BL00010T (TBRC 17198T = NBRC 116413T), and Rhodoferax mekongensis sp. nov., with the type strain D8-11T (TBRC 17307T = NBRC 116415T).

Characterization of bacteria expectorated during forced salivation of the Phlebotomus papatasi: A neglected component of sand fly infectious inoculums

The infectious inoculum of a sand fly, apart from its metacyclic promastigotes, is composed of factors derived from both the parasite and the vector. Vector-derived factors, including salivary proteins and the gut microbiota, are essential for the establishment and enhancement of infection. However, the type and the number of bacteria egested during salivation is unclear. In the present study, sand flies of Phlebotomus papatasi were gathered from three locations in hyperendemic focus of zoonotic cutaneous leishmaniasis (ZCL) in Isfahan Province, Iran. By using the forced salivation assay and targeting the 16S rRNA barcode gene, egested bacteria were characterized in 99 (44%) out of 224 sand flies. Culture-dependent and culture-independent methods identified the members of Enterobacter cloacae and Spiroplasma species as dominant taxa, respectively. Ten top genera of Spiroplasma, Ralstonia, Acinetobacter, Reyranella, Undibacterium, Bryobacter, Corynebacterium, Cutibacterium, Psychrobacter, and Wolbachia constituted >80% of the saliva microbiome. Phylogenetic analysis displayed the presence of only one bacterial species for the Spiroplasma, Ralstonia, Reyranella, Bryobacter and Wolbachia, two distinct species for Cutibacterium, three for Undibacterium and Psychrobacter, 16 for Acinetobacter, and 27 for Corynebacterium, in the saliva. The abundance of microbes in P. papatasi saliva was determined by incorporating the data on the read counts and the copy number of 16S rRNA gene, about 9,000 bacterial cells, per sand fly. Both microbiological and metagenomic data indicate that bacteria are constant companions of Leishmania, from the intestine of the vector to the vertebrate host. This is the first forced salivation experiment in a sand fly, addressing key questions on infectious bite and competent vectors.

Current Trends and Challenges of Microbiome Research in Prostate Cancer

PURPOSE OF REVIEW

The role of the gut microbiome in prostate cancer is an emerging area of research interest. However, no single causative organism has yet been identified. The goal of this paper is to examine the role of the microbiome in prostate cancer and summarize the challenges relating to methodology in specimen collection, sequencing technology, and interpretation of results.

RECENT FINDINGS

Significant heterogeneity still exists in methodology for stool sampling/storage, preservative options, DNA extraction, and sequencing database selection/in silico processing. Debate persists over primer choice in amplicon sequencing as well as optimal methods for data normalization. Statistical methods for longitudinal microbiome analysis continue to undergo refinement. While standardization of methodology may help yield more consistent results for organism identification in prostate cancer, this is a difficult task due to considerable procedural variation at each step in the process. Further reproducibility and methodology research is required.

Harnessing the intragenomic variability of rRNA operons to improve differentiation of Vibrio species

Although the 16S rRNA gene is frequently used as a phylogenetic marker in analysis of environmental DNA, this marker often fails to distinguish closely related species, including those in the genus Vibrio. Here, we investigate whether inclusion and analysis of 23S rRNA sequence can help overcome the intrinsic weaknesses of 16S rRNA analyses for the differentiation of Vibrio species. We construct a maximum likelihood 16S rRNA gene tree to assess the use of this gene to identify clades of Vibrio species. Within the 16S rRNA tree, we identify the putative informative bases responsible for polyphyly, and demonstrate the association of these positions with tree topology. We demonstrate that concatenation of 16S and 23S rRNA genes increases the number of informative nucleotide positions, thereby overcoming ambiguities in 16S rRNA-based phylogenetic reconstructions. Finally, we experimentally demonstrate that this approach considerably improves the differentiation and identification of Vibrio species in environmental samples.

A longitudinal study of queen health in honey bees reveals tissue specific response to seasonal changes and pathogen pressure

The health of honey bee queens is crucial for colony success, particularly during stressful periods like overwintering. To accompany a previous longitudinal study of colony and worker health, we explored niche-specific gut microbiota, host gene expression, and pathogen prevalence in honey bee queens overwintering in a warm southern climate. We found differential gene expression and bacterial abundance with respect to various pathogens throughout the season. Biologically older queens had larger microbiotas, particularly enriched in Bombella and Bifidobacterium. Both Deformed Wing Virus A and B subtypes were highest in the fat body tissue in January, correlating with colony Varroa levels, and Deformed Wing Virus titers in workers. High viral titers in queens were associated with decreased vitellogenin expression, suggesting a potential trade-off between immune function and reproductive capacity. Additionally, we found a complex and dynamic relationship between these viral loads and immune gene expression, indicating a possible breakdown in the coordinated immune response as the season progressed. Our study also revealed a potential link between Nosema and Melissococcus plutonius infections in queens, demonstrating that seasonal opportunism is not confined to just workers. Overall, our findings highlight the intricate interplay between pathogens, metabolic state, and immune response in honey bee queens. Combined with worker and colony-level metrics from the same colonies, our findings illustrate the social aspect of queen health and resilience over the winter dearth.

Enhancement of cellulase production by cellulolytic bacteria SB125 in submerged fermentation medium and biochemical characterization of the enzyme

Microbial diversity from indigenous cultures has the potential to accelerate lignocellulose degradation through enzymes and make composting economically feasible. Therefore, this study is designed to boost cellulase output from a bacterial strain obtained from soil using a one-variable-at-a-time approach and response surface methodology. The bacteria recognized as Bacillus tequilensis (ON754229) produced the maximum cellulase at a temperature of 37 °C, pH -7.0, and incubation time of 72 h. A major contribution was anticipated by glucose (17 %) and ammonium sulfate (11 %) with cellulase activity of 0.56 U/mL in the optimized medium. The enzyme possessed activity of CMCase, FPase, and amylase of 0.589 μmol/min, 1.22 μmol/min, and 0.92 μmol/min respectively. SDS-PAGE showed a 65 kDa molecular weight of the enzyme capable of degrading cellulose, as confirmed by zymogram analysis. The enzyme showed relatively moderate thermo-stability towards neutral pH conditions possessing optimum conditions at pH 6.5 and temperature of 50 °C. The Km and Vmax values were 11.44 mM and 0.643 μmol/min respectively. The presence of MgSO4, ZnSO4, and Triton X- 100 increased the enzymatic reaction however AgNO3, EDTA, and HgCl2 altered the activation process. These results showed cellulase from B. tequilensis SB125 would be suitable for conventional industrial processes that convert biomass into biofuels.

Chromosomal barcodes for simultaneous tracking of near-isogenic bacterial strains in plant microbiota

DNA-amplicon-based microbiota profiling can estimate species diversity and abundance but cannot resolve genetic differences within individuals of the same species. Here we report the development of modular bacterial tags (MoBacTags) encoding DNA barcodes that enable tracking of near-isogenic bacterial commensals in an array of complex microbiome communities. Chromosomally integrated DNA barcodes are then co-amplified with endogenous marker genes of the community by integrating corresponding primer binding sites into the barcode. We use this approach to assess the contributions of individual bacterial genes to Arabidopsis thaliana root microbiota establishment with synthetic communities that include MoBacTag-labelled strains of Pseudomonas capeferrum. Results show reduced root colonization for certain mutant strains with defects in gluconic-acid-mediated host immunosuppression, which would not be detected with traditional amplicon sequencing. Our work illustrates how MoBacTags can be applied to assess scaling of individual bacterial genetic determinants in the plant microbiota.

Linking antibiotic resistance gene patterns with advanced faecal pollution assessment and environmental key parameters along 2300 km of the Danube River

The global spread of antimicrobial resistance (AMR) in the environment is a growing health threat. Large rivers are of particular concern as they are highly impacted by wastewater discharge while being vital lifelines serving various human needs. A comprehensive understanding of occurrence, spread and key drivers of AMR along whole river courses is largely lacking. We provide a holistic approach by studying spatiotemporal patterns and hotspots of antibiotic resistance genes (ARGs) along 2311 km of the navigable Danube River, combining a longitudinal and temporal monitoring campaign. The integration of advanced faecal pollution diagnostics and environmental and chemical key parameters allowed linking ARG concentrations to the major pollution sources and explaining the observed patterns. Nine AMR markers, including genes conferring resistance to five different antibiotic classes of clinical and environmental relevance, and one integrase gene were determined by probe-based qPCR. All AMR targets could be quantified in Danube River water, with intI1 and sul1 being ubiquitously abundant, qnrS, tetM, blaTEM with intermediate abundance and blaOXA-48like, blaCTX-M-1 group, blaCTX-M-9 group and blaKPC genes with rare occurrence. Human faecal pollution from municipal wastewater discharges was the dominant factor shaping ARG patterns along the Danube River. Other significant correlations of specific ARGs were observed with discharge, certain metals and pesticides. In contrast, intI1 was not associated with wastewater but was already established in the water microbiome. Animal contamination was detected only sporadically and was correlated with ARGs only in the temporal sampling set. During temporal monitoring, an extraordinary hotspot was identified emphasizing the variability within natural waters. This study provides the first comprehensive baseline concentrations of ARGs in the Danube River and lays the foundation for monitoring future trends and evaluating potential reduction measures. The applided holistic approach proved to be a valuable methodological contribution towards a better understanding of the environmental occurrence of AMR.

Effect of model methanogens on the electrochemical activity, stability, and microbial community structure of Geobacter spp. dominated biofilm anodes

Combining anaerobic digestion (AD) and microbial electrochemical technologies (MET) in AD-MET holds great potential. Methanogens have been identified as one cause of decreased electrochemical activity and deterioration of Geobacter spp. biofilm anodes. A better understanding of the different interactions between methanogenic genera/species and Geobacter spp. biofilms is needed to shed light on the observed reduction in electrochemical activity and stability of Geobacter spp. dominated biofilms as well as observed changes in microbial communities of AD-MET. Here, we have analyzed electrochemical parameters and changes in the microbial community of Geobacter spp. biofilm anodes when exposed to three representative methanogens with different metabolic pathways, i.e., Methanosarcina barkeri, Methanobacterium formicicum, and Methanothrix soehngenii. M. barkeri negatively affected the performance and stability of Geobacter spp. biofilm anodes only in the initial batches. In contrast, M. formicicum did not affect the stability of Geobacter spp. biofilm anodes but caused a decrease in maximum current density of ~37%. M. soehngenii induced a coloration change of Geobacter spp. biofilm anodes and a decrease in the total transferred charge by ~40%. Characterization of biofilm samples after each experiment by 16S rRNA metabarcoding, whole metagenome nanopore sequencing, and shotgun sequencing showed a higher relative abundance of Geobacter spp. after exposure to M. barkeri as opposed to M. formicicum or M. soehngenii, despite the massive biofilm dispersal observed during initial exposure to M. barkeri.

Optimizing electrochemically active microorganisms as a key player in the bioelectrochemical system: Identification methods and pathways to large-scale implementation

The rapid global economic growth driven by industrialization and population expansion has resulted in significant issues, including reliance on fossil fuels, energy scarcity, water crises, and environmental emissions. To address these issues, bioelectrochemical systems (BES) have emerged as a dual-purpose solution, harnessing electrochemical processes and the capabilities of electrochemically active microorganisms (EAM) to simultaneously recover energy and treat wastewater. This review examines critical performance factors in BES, including inoculum selection, pretreatment methods, electrodes, and operational conditions. Further, authors explore innovative approaches to suppress methanogens and simultaneously enhance the EAM in mixed cultures. Additionally, advanced techniques for detecting EAM are discussed. The rapid detection of EAM facilitates the selection of suitable inoculum sources and optimization of enrichment strategies in BESs. This optimization is essential for facilitating the successful scaling up of BES applications, contributing substantially to the realization of clean energy and sustainable wastewater treatment. This analysis introduces a novel viewpoint by amalgamating contemporary research on the selective enrichment of EAM in mixed cultures. It encompasses identification and detection techniques, along with methodologies tailored for the selective enrichment of EAM, geared explicitly toward upscaling applications in BES.

Monitoring the Photorhabdus spp. bacterial load in Heterorhabditis bacteriophora dauer juveniles over different storage times and temperatures: A molecular approach

Biological control products based on the entomopathogenic nematode Heterorhabditis bacteriophora can vary in virulence (quality). The influence of their symbiotic bacteria Photorhabdus spp. inside the infective dauer juvenile (DJ) on DJ quality has not received much attention in the past. The presence of the bacteria in the DJ is crucial for its biocontrol potential. This investigation provides a method to quantify the bacterial load inside the DJ based on a qPCR technique. Information from the genome of Photorhabdus laumondii strain DE2 was used to identify single copy genes with no homology to any other bacterial accessions. One gene (hereby named CG2) was selected for primers design and for further qPCR experiments. Cross-amplification tests with P. thracensis and P. kayaii, also symbionts of H. bacteriophora, were positive, whereas no amplicons were produced for P. temperata or Xenorhabdus nematophila. We tested our qPCR system in DJ populations carrying defined proportions of bacteria-free (axenic) vs bacteria-carrying nematodes. With an increasing proportion of axenic DJ in a population, virulence declined, and the virulence was proportional to the amount of bacterial DNA detected in the population by qPCR. Along liquid storage over long time, virulence also decreased, and this factor correlated with the reduction of bacterial DNA on the respective DJ population. We observed that stored DJ kept virulent up to 90 days and thereafter the virulence as well as the amount of bacterial DNA drastically decreased. Storage temperature also influenced the bacterial survival. Inside formulated DJ, the loss of bacterial DNA on the DJ population was accelerated under storage temperatures below 7.5 °C, suggesting that reproduction of the bacterial cells takes place when growth temperature is favorable. The role of bacterial survival inside stored DJ can now be adequately addressed using this molecular quality-control technique.

Genomic attributes of airway commensal bacteria and mucosa

Microbial communities at the airway mucosal barrier are conserved and highly ordered, in likelihood reflecting co-evolution with human host factors. Freed of selection to digest nutrients, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the initial results of systematic culture and whole-genome sequencing of the thoracic airway bacteria, identifying 52 novel species amongst 126 organisms that constitute 75% of commensals typically present in heathy individuals. Clinically relevant genes encode antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. Using whole-genome content we identify dysbiotic features that may influence asthma and chronic obstructive pulmonary disease. We match isolate gene content to transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways to sustain host interactions with microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosa in lung diseases of global significance.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

Improved Equine Fecal Microbiome Characterization Using Target Enrichment by Hybridization Capture

GITDs are among the most common causes of death in adult and young horses in the United States (US). Previous studies have indicated a connection between GITDs and the equine gut microbiome. However, the low taxonomic resolution of the current microbiome sequencing methods has hampered the identification of specific bacterial changes associated with GITDs in horses. Here, we have compared TEHC, a new approach for 16S rRNA gene selection and sequencing, with conventional 16S rRNA gene amplicon sequencing for the characterization of the equine fecal microbiome. Both sequencing approaches were used to determine the fecal microbiome of four adult horses and one commercial mock microbiome. Our results show that TEHC yielded significantly more operational taxonomic units (OTUs) than conventional 16S amplicon sequencing when the same number of reads were used in the analysis. This translated into a deeper and more accurate characterization of the fecal microbiome when the samples were sequenced with TEHC according to the relative abundance analysis. Alpha and beta diversity metrics corroborated these findings and demonstrated that the microbiome of the fecal samples was significantly richer when sequenced with TEHC compared to 16S amplicon sequencing. Altogether, our study suggests that the TEHC strategy provides a more extensive characterization of the fecal microbiome of horses than the current alternative based on the PCR amplification of a portion of the 16S rRNA gene.

A longitudinal field study of commercial honey bees shows that non-native probiotics do not rescue antibiotic treatment, and are generally not beneficial

Probiotics are widely used in agriculture including commercial beekeeping, but there is little evidence supporting their effectiveness. Antibiotic treatments can greatly distort the gut microbiome, reducing its protective abilities and facilitating the growth of antibiotic resistant pathogens. Commercial beekeepers regularly apply antibiotics to combat bacterial infections, often followed by an application of non-native probiotics advertised to ease the impact of antibiotic-induced gut dysbiosis. We tested whether probiotics affect the gut microbiome or disease prevalence, or rescue the negative effects of antibiotic induced gut dysbiosis. We found no difference in the gut microbiome or disease markers by probiotic application or antibiotic recovery associated with probiotic treatment. A colony-level application of the antibiotics oxytetracycline and tylosin produced an immediate decrease in gut microbiome size, and over the longer-term, very different and persistent dysbiotic effects on the composition and membership of the hindgut microbiome. Our results demonstrate the lack of probiotic effect or antibiotic rescue, detail the duration and character of dysbiotic states resulting from different antibiotics, and highlight the importance of the gut microbiome for honeybee health.

Megasphaera elsdenii: Its Role in Ruminant Nutrition and Its Potential Industrial Application for Organic Acid Biosynthesis

The Gram-negative, strictly anaerobic bacterium Megasphaera elsdenii was first isolated from the rumen in 1953 and is common in the mammalian gastrointestinal tract. Its ability to use either lactate or glucose as its major energy sources for growth has been well documented, although it can also ferment amino acids into ammonia and branched-chain fatty acids, which are growth factors for other bacteria. The ruminal abundance of M. elsdenii usually increases in animals fed grain-based diets due to its ability to use lactate (the product of rapid ruminal sugar fermentation), especially at a low ruminal pH (<5.5). M. elsdenii has been proposed as a potential dietary probiotic to prevent ruminal acidosis in feedlot cattle and high-producing dairy cows. However, this bacterium has also been associated with milk fat depression (MFD) in dairy cows, although proving a causative role has remained elusive. This review summarizes the unique physiology of this intriguing bacterium and its functional role in the ruminal community as well as its role in the health and productivity of the host animal. In addition to its effects in the rumen, the ability of M. elsdenii to produce C2-C7 carboxylic acids-potential precursors for industrial fuel and chemical production-is examined.

Unveiling the crucial role of soil microorganisms in carbon cycling: A review

Soil microorganisms, by actively participating in the decomposition and transformation of organic matter through diverse metabolic pathways, play a pivotal role in carbon cycling within soil systems and contribute to the stabilization of organic carbon, thereby influencing soil carbon storage and turnover. Investigating the processes, mechanisms, and driving factors of soil microbial carbon cycling is crucial for understanding the functionality of terrestrial carbon sinks and effectively addressing climate change. This review comprehensively discusses the role of soil microorganisms in soil carbon cycling from three perspectives: metabolic pathways, microbial communities, and environmental influences. It elucidates the roles of different microbial species in carbon cycling and highlights the impact of microbial interactions and environmental factors on carbon cycling. Through the synthesis of 2171 relevant papers in the Web of Science Core database, we elucidated the ecological community structure, activity, and assembly mechanisms of soil microorganisms crucial to the soil carbon cycle that have been widely analyzed. The integration of soil microbial carbon cycle and its driving factors are vital for accurately predicting and modeling biogeochemical cycles and effectively addressing the challenges posed by global climate change. Such integration is vital for accurately predicting and modeling biogeochemical cycles and effectively addressing the challenges posed by global climate change.

Ecological assessment of combined sewer overflow management practices through the analysis of benthic and hyporheic sediment bacterial assemblages from an intermittent stream

Combined sewer overflows (CSO) are used to avoid overloading unitary sewers and wastewater treatment plants. Following the European Council Directive on Urban Wastewater Treatment (UWT), CSO discharges are regulated using guidelines that aim to reduce their ecological impact on aquatic systems. A model CSO, which is part of a long-term experimental field observatory, was modified according to these guidelines and used to evaluate the benefits of compliance through analyses of the bacteriological and chemical states of the receiving intermittent stream. The benthic and hyporheic sediments of similar geomorphic units located upstream and downstream of a monitored CSO outlet were compared before and after changes in CSO regimes. Hydrological, pollutants (Metal Trace Elements, MTE; Polycyclic Aromatic Hydrocarbons, PAH; fecal indicator bacteria, FIB), and tpm-based DNA meta-barcoding datasets resolving the occurrences of >700 bacterial species of nearly 200 genera were studied. The frequency of overflow was confirmed to have significantly decreased following the application of the UWT guidelines. Overflows became almost limited to periods of heavy summer thunderstorm events. These changes were not associated with a significant decrease in most of the surveyed MTE, PAH, and FIB among stream sediments, except for chromium. Ecological benefits were highlighted by significant changes in tpm-based meta-barcoding community patterns between the UWT compliant sampling period and the previous one. Bacterial community change point analyses confirmed this segregation in the meta-barcoding dataset according to hydrological indices such as the number of CSO events and discharged volumes. A significant decline in CSO bacterial taxa in the benthic and hyporheic sediments was observed. Thirty-four CSO indicator species were identified, including Aeromonas caviae, Aeromonas media, and Pseudomonas oleovorans. These indicators, often documented as opportunistic pathogens (to humans, animals or plants) and/or pollutant degraders, were proposed as ecological sentinels for the assessment of CSO impacts.

Disentangling microbial networks across pelagic zones in the tropical and subtropical global ocean

Microbial interactions are vital in maintaining ocean ecosystem function, yet their dynamic nature and complexity remain largely unexplored. Here, we use association networks to investigate possible ecological interactions in the marine microbiome among archaea, bacteria, and picoeukaryotes throughout different depths and geographical regions of the tropical and subtropical global ocean. Our findings reveal that potential microbial interactions change with depth and geographical scale, exhibiting highly heterogeneous distributions. A few potential interactions were global, meaning they occurred across regions at the same depth, while 11-36% were regional within specific depths. The bathypelagic zone had the lowest proportion of global associations, and regional associations increased with depth. Moreover, we observed that most surface water associations do not persist in deeper ocean layers despite microbial vertical dispersal. Our work contributes to a deeper understanding of the tropical and subtropical global ocean interactome, which is essential for addressing the challenges posed by global change.

From hype to hope: Considerations in conducting robust microbiome science

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

Microbial diversity and abundance vary along salinity, oxygen, and particle size gradients in the Chesapeake Bay

Marine snow and other particles are abundant in estuaries, where they drive biogeochemical transformations and elemental transport. Particles range in size, thereby providing a corresponding gradient of habitats for marine microorganisms. We used standard normalized amplicon sequencing, verified with microscopy, to characterize taxon-specific microbial abundances, (cells per litre of water and per milligrams of particles), across six particle size classes, ranging from 0.2 to 500 μm, along the main stem of the Chesapeake Bay estuary. Microbial communities varied in salinity, oxygen concentrations, and particle size. Many taxonomic groups were most densely packed on large particles (in cells/mg particles), yet were primarily associated with the smallest particle size class, because small particles made up a substantially larger portion of total particle mass. However, organisms potentially involved in methanotrophy, nitrite oxidation, and sulphate reduction were found primarily on intermediately sized (5-180 μm) particles, where species richness was also highest. All abundant ostensibly free-living organisms, including SAR11 and Synecococcus, appeared on particles, albeit at lower abundance than in the free-living fraction, suggesting that aggregation processes may incorporate them into particles. Our approach opens the door to a more quantitative understanding of the microscale and macroscale biogeography of marine microorganisms.

Microbiome in a ground-based analog cabin of China Space Station during a 50-day human occupation

Dead-corner areas in space station that untouched by the clean-up campaign often experience microorganisms outbreaks, but the microbiome of these areas has never been studied. In this study, the microbiome in a ground-based analog ``Tianhe'' core module of China Space Station was first investigated during a 50-day three-crew occupation. Dead-corner areas were receiving attention by adopting a new sampling method. Results indicate that the astronauts occupation did not affect the dominant bacteria community, but affected a small proportion. Due to the frequent activity of astronauts in the work and sleep areas, the biomarkers in these two areas are common human skin surface and gut microorganisms, respectively. For areas that astronaut rarely visits, the biomarkers in which are common environmental microbial groups. Fluorescence counting showed that 70.12-84.78% of bacteria were alive, with a quantity of 104-105 cells/100 cm2. With the occupation time extension, the number of microorganisms increased. At the same sampling time, there was no significant bioburden difference in various locations. The cultivable bioburden ranged from 101 to 104 colony forming unit (CFU)/100 cm2, which are the following eight genera Penicillium, Microsphaeropsis, Stachybotrys, Humicola, Cladosporium, Bacillus, Planomicrobium, and Acinetobacter. Chryseomicrobium genus may be a key focus for future microbial prevention and control work.

Aerosolized Cyanobacterial Harmful Algal Bloom Toxins: Microcystin Congeners Quantified in the Atmosphere

Cyanobacterial harmful algal blooms (cHABs) have the potential to adversely affect public health through the production of toxins such as microcystins, which consist of numerous molecularly distinct congeners. Microcystins have been observed in the atmosphere after emission from freshwater lakes, but little is known about the health effects of inhaling microcystins and the factors contributing to microcystin aerosolization. This study quantified total microcystin concentrations in water and aerosol samples collected around Grand Lake St. Marys (GLSM), Ohio. Microcystin concentrations in water samples collected on the same day ranged from 13 to 23 μg/L, dominated by the d-Asp3-MC-RR congener. In particulate matter <2.5 μm (PM2.5), microcystin concentrations up to 156 pg/m3 were detected; the microcystins were composed primarily of d-Asp3-MC-RR, with additional congeners (d-Asp3-MC-HtyR and d-Asp3-MC-LR) observed in a sample collected prior to a storm event. The PM size fraction containing the highest aerosolized MC concentration ranged from 0.44 to 2.5 μm. Analysis of total bacteria by qPCR targeting 16S rDNA revealed concentrations up to 9.4 × 104 gc/m3 in aerosol samples (≤3 μm), while a marker specific to cyanobacteria was not detected in any aerosol samples. Concentrations of aerosolized microcystins varied even when concentrations in water were relatively constant, demonstrating the importance of meteorological conditions (wind speed and direction) and aerosol generation mechanism(s) (wave breaking, spillway, and aeration systems) when evaluating inhalation exposure to microcystins and subsequent impacts on human health.

Premise Plumbing Pipe Materials and In-Building Disinfectants Shape the Potential for Proliferation of Pathogens and Antibiotic Resistance Genes

In-building disinfectants are commonly applied to control the growth of pathogens in plumbing, particularly in facilities such as hospitals that house vulnerable populations. However, their application has not been well optimized, especially with respect to interactive effects with pipe materials and potential unintended effects, such as enrichment of antibiotic resistance genes (ARGs) across the microbial community. Here, we used triplicate convectively mixed pipe reactors consisting of three pipe materials (PVC, copper, and iron) for replicated simulation of the distal reaches of premise plumbing and evaluated the effects of incrementally increased doses of chlorine, chloramine, chlorine dioxide, and copper-silver disinfectants. We used shotgun metagenomic sequencing to characterize the resulting succession of the corresponding microbiomes over the course of 37 weeks. We found that both disinfectants and pipe material affected ARG and microbial community taxonomic composition both independently and interactively. Water quality and total bacterial numbers were not found to be predictive of pathogenic species markers. One result of particular concern was the tendency of disinfectants, especially monochloramine, to enrich ARGs. Metagenome assembly indicated that many ARGs were enriched specifically among the pathogenic species. Functional gene analysis was indicative of a response of the microbes to oxidative stress, which is known to co/cross-select for antibiotic resistance. These findings emphasize the need for a holistic evaluation of pathogen control strategies for plumbing.

Multicenter evaluation of gut microbiome profiling by next-generation sequencing reveals major biases in partial-length metabarcoding approach

Next-generation sequencing workflows, using either metabarcoding or metagenomic approaches, have massively contributed to expanding knowledge of the human gut microbiota, but methodological bias compromises reproducibility across studies. Where these biases have been quantified within several comparative analyses on their own, none have measured inter-laboratory reproducibility using similar DNA material. Here, we designed a multicenter study involving seven participating laboratories dedicated to partial- (P1 to P5), full-length (P6) metabarcoding, or metagenomic profiling (MGP) using DNA from a mock microbial community or extracted from 10 fecal samples collected at two time points from five donors. Fecal material was collected, and the DNA was extracted according to the IHMS protocols. The mock and isolated DNA were then provided to the participating laboratories for sequencing. Following sequencing analysis according to the laboratories' routine pipelines, relative taxonomic-count tables defined at the genus level were provided and analyzed. Large variations in alpha-diversity between laboratories, uncorrelated with sequencing depth, were detected among the profiles. Half of the genera identified by P1 were unique to this partner and two-thirds of the genera identified by MGP were not detected by P3. Analysis of beta-diversity revealed lower inter-individual variance than inter-laboratory variances. The taxonomic profiles of P5 and P6 were more similar to those of MGP than those obtained by P1, P2, P3, and P4. Reanalysis of the raw sequences obtained by partial-length metabarcoding profiling, using a single bioinformatic pipeline, harmonized the description of the bacterial profiles, which were more similar to each other, except for P3, and closer to the profiles obtained by MGP. This study highlights the major impact of the bioinformatics pipeline, and primarily the database used for taxonomic annotation. Laboratories need to benchmark and optimize their bioinformatic pipelines using standards to monitor their effectiveness in accurately detecting taxa present in gut microbiota.

Metagenomics and metabolomics approaches in the study of Candida albicans colonization of host niches: a framework for finding microbiome-based antifungal strategies

In silico and experimental approaches have allowed an ever-growing understanding of the interactions within the microbiota. For instance, recently acquired data have increased knowledge of the mechanisms that support, in the gut and vaginal microbiota, the resistance to colonization by Candida albicans, an opportunistic fungal pathogen whose overgrowth can initiate severe infections in immunocompromised patients. Here, we review how bacteria from the microbiota interact with C. albicans. We show how recent OMICs-based pipelines, using metagenomics and/or metabolomics, have identified bacterial species and metabolites modulating C. albicans growth. We finally discuss how the combined use of cutting-edge OMICs-based and experimental approaches could provide new means to control C. albicans overgrowth within the microbiota and prevent its consequences.

Microbial symbionts are shared between ants and their associated beetles

The transmission of microbial symbionts across animal species could strongly affect their biology and evolution, but our understanding of transmission patterns and dynamics is limited. Army ants (Formicidae: Dorylinae) and their hundreds of closely associated insect guest species (myrmecophiles) can provide unique insights into interspecific microbial symbiont sharing. Here, we compared the microbiota of workers and larvae of the army ant Eciton burchellii with those of 13 myrmecophile beetle species using 16S rRNA amplicon sequencing. We found that the previously characterized specialized bacterial symbionts of army ant workers were largely absent from ant larvae and myrmecophiles, whose microbial communities were usually dominated by Rickettsia, Wolbachia, Rickettsiella and/or Weissella. Strikingly, different species of myrmecophiles and ant larvae often shared identical 16S rRNA genotypes of these common bacteria. Protein-coding gene sequences confirmed the close relationship of Weissella strains colonizing army ant larvae, some workers and several myrmecophile species. Unexpectedly, these strains were also similar to strains infecting dissimilar animals inhabiting very different habitats: trout and whales. Together, our data show that closely interacting species can share much of their microbiota, and some versatile microbial species can inhabit and possibly transmit across a diverse range of hosts and environments.

Ammonium oxidizing bacterial populations in South African activated sludge wastewater treatment plants

This is the first study that describes ammonium oxidizing bacterial populations and correlations of these populations with a range of criteria in activated sludge wastewater treatment plants in South Africa. In this study, not only the influent but also the activated sludge chemistry was comprehensively characterized. Multivariate statistical analyses were used to determine the relative significances of the geographical location (factor: site), wastewater treatment plant process (factor: configuration), seasonality (factor: season), and environmental parameters on the ammonium oxidizing bacterial genera in six municipal activated sludge wastewater treatments plants from two sites (the cities of Cape Town and Ekurhuleni). The geographical location (site) was significant for selection of the ammonium oxidizing genera (Global ANOSIM R value = 0.538, p = 0.001). It was established that the inter-site differences were not climatic in origin, nor related to the composition of the influent, but were rather driven by the activated sludge chemistry. It was found using BEST analysis that the activated sludge ammonia, activated sludge total phosphate, and activated sludge total chemical oxygen demand were the most significant (p < 0.001) drivers for ammonium oxidizing bacterial selection (ANOSIM Global R value 0.419) and were significantly higher in the activated sludge from the City of Cape Town wastewater treatment plants. Nitrosospira was the most abundant ammonium oxidizing bacterial genus, with notably higher relative and estimated actual abundances in the City of Cape Town wastewater treatment plants than the City of Ekurhuleni wastewater treatment plants. The strong selection of Nitrosospira in the City of Cape Town wastewater treatment plants with higher nutrient concentrations strongly suggests that high concentrations of activated sludge ammonia, activated sludge total phosphate, and activated sludge total chemical oxygen demand are key selective drivers for this genus. PRACTITIONER POINTS: First comprehensive study describing ammonium oxidizing bacterial populations in Southern African domestic activated sludge wastewater treatment plants. The geographical location (site) was significant for selection of different ammonium oxidizing genera (Global ANOSIM R value = 0.538, p = 0.001). Inter-site differences driven by the activated sludge chemistry, not climate or influent wastewater composition. Selection of Nitrosospira driven by high concentrations of activated sludge ammonia, total phosphate and total chemical oxygen demand.

Effect of carbon nanomaterials on functional diversity and structure of soil microbial community under single and repeated exposures

The extensive application of carbon nanomaterials (CNMs) has attracted increasing studies concerned about its environmental impact. These studies focus on single exposure to CNMs, but repeated exposures with relatively low concentration are more likely to occur under actual exposure scenario. In this study, we studied the metabolic functional and structure of soil microorganism community under single and repeated exposures to multiwalled carbon nanotubes (MW), graphene (GR), and fullerene (C60) by Biolog EcoPlates and high-throughput sequencing. Our findings revealed that repeated exposures to CNMs significantly increase the metabolic activity and diversity of the soil microbial community as compared with single exposure. Principal component and similarity analysis not only indicated that GR exerted a stronger effect on soil microbial diversity among three exposures compared to C60 and MW, but also revealed that the metabolic activity of the soil microbial community was more affected by the exposure scenarios of CNMs than the type of CNMs. These findings elucidated the effect of CNMs under different exposure scenarios on soil microorganism community, providing a new perspective on the risk assessment of nanomaterials.

GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.

Learning from the unknown: exploring the range of bacterial functionality

Determining the repertoire of a microbe's molecular functions is a central question in microbial biology. Modern techniques achieve this goal by comparing microbial genetic material against reference databases of functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here, we describe a novel approach to exploring bacterial functional repertoires without reference databases. Our Fusion scheme establishes functional relationships between bacteria and assigns organisms to Fusion-taxa that differ from otherwise defined taxonomic clades. Three key findings of our work stand out. First, bacterial functional comparisons outperform marker genes in assigning taxonomic clades. Fusion profiles are also better for this task than other functional annotation schemes. Second, Fusion-taxa are robust to addition of novel organisms and are, arguably, able to capture the environment-driven bacterial diversity. Finally, our alignment-free nucleic acid-based Siamese Neural Network model, created using Fusion functions, enables finding shared functionality of very distant, possibly structurally different, microbial homologs. Our work can thus help annotate functional repertoires of bacterial organisms and further guide our understanding of microbial communities.

Correlation between Bacterial Cell Density and Abundance of Antibiotic Resistance on Milking Machine Surfaces Assessed by Cultivation and Direct qPCR Methods

The relative abundance of antibiotic-resistant bacteria and antibiotic-resistance genes was surveyed for different parts of a milking machine. A cultivation approach based on swab samples showed a highly diverse microbiota, harboring resistances against cloxacillin, ampicillin, penicillin, and tetracycline. This approach demonstrated a substantial cloxacillin resistance of numerous taxa within milking machine microbiota coming along with regular use of cloxacillin for dry-off therapy of dairy cows. For the less abundant tetracycline-resistant bacteria we found a positive correlation between microbial cell density and relative abundance of tetracycline-resistant microorganisms (R2 = 0.73). This indicated an accelerated dispersion of resistant cells for sampling locations with high cell density. However, the direct quantification of the tetM gene from the swap samples by qPCR showed the reverse relation to bacterial density if normalized against the abundance of 16S rRNA genes (R2 = 0.88). The abundance of 16S rRNA genes was analyzed by qPCR combined with a propidium monoazide treatment, which eliminates 16S rRNA gene signals in negative controls.

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

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

West-Siberian Chernozem: How Vegetation and Tillage Shape Its Bacteriobiome

Managing soil biodiversity using reduced tillage is a popular approach, yet soil bacteriobiomes in the agroecosystems of Siberia has been scarcely studied, especially as they are related to tillage. We studied bacteriobiomes in Chernozem under natural steppe vegetation and cropped for wheat using conventional or no tillage in a long-term field trial in the Novosibirsk region, Russia, by using the sequence diversity of the V3/V4 region of 16S rRNA genes. Actinobacteria, Acidobacteria, and Proteobacteria summarily accounted for 80% of the total number of sequences, with Actinobacteria alone averaging 51%. The vegetation (natural vs. crop) and tillage (ploughed vs. no-till) affected the bacterial relative abundance at all taxonomic levels and many taxa, e.g., hundreds of OTUs. However, such changes did not translate into α-biodiversity changes, i.e., observed and potential OTUs' richness, Shannon, and Simpson, excepting the slightly higher evenness and equitability in the top 0-5 cm of the undisturbed soil. As for the β-biodiversity, substituting conventional ploughing with no tillage and maintaining the latter for 12 years notably shifted the soil bacteriobiome closer to the one in the undisturbed soil. This study, presenting the first inventory of soil bacteriobiomes under different tillage in the south of West Siberia, underscores the need to investigate the seasonality and longevity aspects of tillage, especially as they are related to crop production.

Machine learning approaches in microbiome research: challenges and best practices

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To assist decision-making, we offer a set of recommendations on algorithm selection, pipeline creation and evaluation, stemming from the COST Action ML4Microbiome. We compared the suggested approaches on a multi-cohort shotgun metagenomics dataset of colorectal cancer patients, focusing on their performance in disease diagnosis and biomarker discovery. It is demonstrated that the use of compositional transformations and filtering methods as part of data preprocessing does not always improve the predictive performance of a model. In contrast, the multivariate feature selection, such as the Statistically Equivalent Signatures algorithm, was effective in reducing the classification error. When validated on a separate test dataset, this algorithm in combination with random forest modeling, provided the most accurate performance estimates. Lastly, we showed how linear modeling by logistic regression coupled with visualization techniques such as Individual Conditional Expectation (ICE) plots can yield interpretable results and offer biological insights. These findings are significant for clinicians and non-experts alike in translational applications.

Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.

Feed Regime Slightly Modifies the Bacterial but Not the Fungal Communities in the Intestinal Mucosal Microbiota of Cobia Fish (Rachycentron canadum)

The bacterial community of the intestinal microbiota influences many host functions, and similar effects have been recently reported for the fungal community (mycobiota). Cobia is a tropical fish that has been studied for its potential in marine aquaculture. However, the study of its bacterial community has been underreported and the mycobiota has not been investigated. We analyzed the gut bacterial and fungal profile present in the intestinal mucosa of reared adult cobias fed two diets (frozen fish pieces (FFPs) and formulated feed (FF)) for 4 months by sequencing the 16S rRNA (V3-V4) and internal transcribed spacer-2 (ITS2) regions using Illumina NovaSeq 6000. No significant differences in the alpha diversity of the bacterial community were observed, which was dominated by the phyla Proteobacteria (~96%) and Firmicutes (~1%). Cobia fed FF showed higher abundance of 10 genera, mainly UCG-002 (Family Oscillospiraceae) and Faecalibacterium, compared to cobia fed FFPs, which showed higher abundance of 7 genera, mainly Methylobacterium-Methylorubrum and Cutibacterium. The inferred bacterial functions were related to metabolism, environmental information processing and cellular processes; and no differences were found between diets. In mycobiota, no differences were observed in the diversity and composition of cobia fed the two diets. The mycobiota was dominated by the phyla Ascomycota (~88%) and Basidiomycota (~11%). This is the first study to describe the gut bacterial and fungal communities in cobia reared under captive conditions and fed on different diets and to identify the genus Ascobulus as a new member of the core fish mycobiota.