Changes of microbiome in response to supplements with silver nanoparticles in cotton rhizosphere.

The current study focuses on analyzing the effects of supplements containing silver nanoparticles (AgNPs) on plant growth and rhizospheric bacterial communities. Specifically, the impact of AgNP supplements was assessed on both plant growth promoting traits and bacterial communities in the soil. To do this, a screening process was conducted to select bacteria capable of synthesizing AgNPs through extracellular biosynthesis. UV-Visible spectrophotometer, Fourier transform infrared, X-ray diffraction, scanning electron microscope, and field emission scanning electron microscopy all confirmed, produced AgNPs is in agglomerates form. The resulting AgNPs were introduced into soil along with various supplements and their effects were evaluated after 10 days using next generation sequencing (Illumina-16S rDNA V3-V4 region dependent) to analyze changes in bacterial communities. Seed germination, root-shoot biomass and chlorophyll content were used to assess the growth of the cotton plant, whereas the bacterial ability to promote growth was evaluated by measuring its culturable diversity including traits like phosphate solubilization and indole acetic acid production. The variance in Bray-Curtis ß diversity among six selected combinations including control depends largely on the type of added supplements contributing to 95%-97% of it. Moreover, seed germination improves greatly between 63% and 100% at a concentration range of 1.4 to 2.8 mg/L with different types of supplements. Based on the results obtained through this study, it is evident that using AgNPs along with fructose could be an effective tool for promoting Gossypium hirsutum growth and enhancing plant growth traits like profiling rhizospheric bacteria. The results that have been obtained endorse the idea of boosting the growth of rhizospheric bacteria in a natural way when AgNPs are present. Using these supplements in fields that have been contaminated will lead to a better understanding of how ecological succession occurs among rhizospheric bacteria, and what effect it has on the growth of plants.

Microbial population analysis improves the evidential value of faecal traces in forensic investigations.

The forensic science community has a growing interest in microbial population analysis, especially the microbial populations found inside and on the human body. Both their high abundance, microbes outnumber human cells by a factor 10, and their diversity, different sites of the human body harbour different microbial communities, make them an interesting tool for forensics. Faecal material is a type of trace evidence which can be found in a variety of criminal cases, but is often being ignored in forensic investigations. Deriving a human short tandem repeat (STR) profile from a faecal sample can be challenging. However, the microbial communities within faecal material can be of additional criminalistic value in linking a faecal trace to the possible donor. We present a microarray technique in which the faecal microbial community is used to differentiate between faecal samples and developed a decision model to predict the possible common origin of questioned samples. The results show that this technique may be a useful additional tool when no or only partial human STR profiles can be generated.

Controlling Brochothrix thermosphacta as a spoilage risk using in-package atmospheric cold plasma.

Brochothrix thermosphacta is the predominant spoilage microorganism in meat and its control in processing environments is important to maintain meat product quality. Atmospheric cold plasma is of interest for control of pathogenic and spoilage microorganisms in foods. This study ascertained the potential of dielectric barrier discharge atmospheric cold plasma (DBD-ACP) for control of B. thermosphacta, taking microbial and food environment factors into consideration, and investigated the shelf-life of lamb chop after in-package plasma treatment in modified atmosphere. Community profiling was used to assess the treatment effects on the lamb microflora. ACP treatment (80 kV) for 30s inactivated B. thermosphacta populations below detection levels in PBS, while 5 min treatment achieved a 2 Log cycle reduction using a complex meat model medium and attached cells. The antimicrobial efficacy of plasma was reduced but still apparent on lamb chop surface-inoculated with high concentrations of B. thermosphacta. Lamb chop treated under modified atmosphere exhibited reduced microbial growth over the product shelf-life and community profiling showed no evident changes to the microbial populations after the treatment. The overall results indicated potential of ACP to enhance microbial control leading to meat storage life extension through adjusting the modality of treatment.

RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys.

BACKGROUND: Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis. RESULTS: Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion. CONCLUSIONS: RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.

Microbial Community and Metabolome Analysis of the Porcine Intestinal Damage Model Induced by the IPEC-J2 Cell Culture-Adapted Porcine Deltacoronavirus (PDCoV) Infection.

This study was conducted to elucidate the intestinal damage induced by the IPEC-J2 cell culture-passaged PDCoV. The results showed that PDCoV disrupted the intestinal structure and increased intestinal permeability, causing abnormalities in mucosal pathology. Additionally, PDCoV induced an imbalance in the intestinal flora and disturbed its stability. Microbial community profiling revealed bacterial enrichment (e.g., Proteobacteria) and reduction (e.g., Firmicutes and Bacteroidetes) in the PDCoV-inoculated piglet model. In addition, metabolomics analysis indicated that 82 named differential metabolites were successfully quantified, including 37 up-regulated and 45 down-regulated metabolites. Chenodeoxycholic acid, sphingosine, and oleanolic aldehyde levels were reduced in PDCoV-inoculated piglets, while phenylacetylglycine and geranylgeranyl-PP levels were elevated. Correlation analysis indicated a negative correlation between Escherichia-Shigella and choline, succinic acid, creatine, phenyllactate, and hippuric acid. Meanwhile, Escherichia-Shigella was positively correlated with acetylcholine, L-Glutamicacid, and N-Acetylmuramate. Roseburia, Lachnospiraceae_UCG-010, Blautia, and Limosilactobacillus were negatively and positively correlated with sphingosine, respectively. These data suggested PDCoV-inoculated piglets exhibited significant taxonomic perturbations in the gut microbiome, which may result in a significantly altered metabolomic profile.

The hidden microbial ecosystem in the perennial ice from a Pyrenean ice cave.

Over the last years, perennial ice deposits located within caves have awakened interest as places to study microbial communities since they represent unique cryospheric archives of climate change. Since the beginning of the twentieth century, the temperature has gradually increased, and it is estimated that by the end of this century the increase in average temperature could be around 4.0°C. In this context of global warming the ice deposits of the Pyrenean caves are undergoing a significant regression. Among this type of caves, that on the Cotiella Massif in the Southern Pyrenees is one of the southernmost studied in Europe. These types of caves house microbial communities which have so far been barely explored, and therefore their study is necessary. In this work, the microbial communities of the Pyrenean ice cave A294 were identified using metabarcoding techniques. In addition, research work was carried out to analyze how the age and composition of the ice affect the composition of the bacterial and microeukaryotic populations. Finally, the in vivo effect of climate change on the cellular machinery that allow microorganisms to live with increasing temperatures has been studied using proteomic techniques.

Fluorescence in situ hybridization and microbial community profiling analysis of explanted cochlear implants.

BACKGROUND: Cochlear implant (CI) infections affect a small, but significant number of patients. Unremitting infections can lead to explantation. Fluorescence in situ hybridization (FISH) and microbial community profiling (MCP) are methods of studying microbial environments of explanted devices that can provide information to reduce morbidity and costs of infected CIs. AIMS/OBJECTIVES: To describe the results and clinical significance of bacterial analyses conducted on explanted CIs. MATERIAL AND METHODS: Between 2013 and 2017, 12 explanted devices underwent microbiological analysis in addition to the manufacturer's device failure analysis. Patients' clinical history, infection status and outcome were reviewed and correlated with microbial analysis results. RESULTS: From 2013 to 2017, 12 Cochlear™ devices from 11 patients underwent additional MCP or FISH analysis. Five devices were explanted due to suspected implant associated infection, and seven were explanted for other reasons. FISH analysis revealed biofilm presence on all infected devices, only partial correlation of cultures with biofilm composition and confirmation that biofilm formation occurs preferentially at particular device interfaces and geometries. MCP analysis presented challenges in data analysis inherent to its technique but correlated with cultures of infected devices and suggested a diverse microbial composition of explanted devices. CONCLUSIONS AND SIGNIFICANCE: Microbial analysis of explanted devices can aid in further elucidating treatment approaches to infected CIs.

Glacial Ice Age Shapes Microbiome Composition in a Receding Southern European Glacier.

Glaciers and their microbiomes are exceptional witnesses of the environmental conditions from remote times. Climate change is threatening mountain glaciers, and especially those found in southern Europe, such as the Monte Perdido Glacier (northern Spain, Central Pyrenees). This study focuses on the reconstruction of the history of microbial communities over time. The microorganisms that inhabit the Monte Perdido Glacier were identified using high-throughput sequencing, and the microbial communities were compared along an altitudinal transect covering most of the preserved ice sequence in the glacier. The results showed that the glacial ice age gradient did shape the diversity of microbial populations, which presented large differences throughout the last 2000 years. Variations in microbial community diversity were influenced by glacial conditions over time (nutrient concentration, chemical composition, and ice age). Some groups were exclusively identified in the oldest samples as the bacterial phyla Fusobacteria and Calditrichaeota, or the eukaryotic class Rhodophyceae. Among groups only found in modern samples, the green sulfur bacteria (phylum Chlorobi) stood out, as well as the bacterial phylum Gemmatimonadetes and the eukaryotic class Tubulinea. A patent impact of human contamination was also observed on the glacier microbiome. The oldest samples, corresponding to the Roman Empire times, were influenced by the beginning of mining exploitation in the Pyrenean area, with the presence of metal-tolerant microorganisms. The most recent samples comprise 600-year-old ancient ice in which current communities are living.

Multicenter assessment of microbial community profiling using 16S rRNA gene sequencing and shotgun metagenomic sequencing.

INTRODUCTION: Microbiome research based on high-throughput sequencing has grown exponentially in recent years, but methodological variations can easily undermine the reproducibility across studies. OBJECTIVES: To systematically evaluate the comparability of sequencing results of 16S rRNA gene sequencing (16Ss)- and shotgun metagenomic sequencing (SMs)-based microbial community profiling in laboratories under routine conditions. METHODS: We designed a multicenter study across 35 participating laboratories in China using designed mock communities and homogenized fecal samples. RESULTS: A wide range of practices and approaches was reported by the participating laboratories. The observed microbial compositions of the mock communities in 46.2% (12/26) of the 16Ss and 82.6% (19/23) of the SMs laboratories had significant correlations with the expected result (Spearman r>0.59, P <0.05). The results from laboratories with near-identical protocols showed slight interlaboratory deviations. However, a high degree of interlaboratory deviation was found in the observed abundances of specific taxa, such as Bacteroides spp. (range: 0.3%-53.5%), Enterococci spp. (range: 0.8%-43.9%) and Fusobacterium spp. (range: 0.1%-39.8%). SMs performed better than 16Ss in detecting low-abundance bacteria (B. bifidum). The differences in DNA extraction methods, amplified regions and bioinformatics analysis tools (taxonomic classifiers and database) were important factors causing interlaboratory deviations. Addressing laboratory contamination is an urgent task because various sources of unexpected microbes were found in negative control samples. CONCLUSIONS: Well-defined control samples, such as the mock communities in this study, should be routinely used in microbiome research for monitoring potential biases. The findings in this study will provide guidance in the choice of more reasonable operating procedures to minimize potential methodological biases in revealing human microbiota composition.

Impact of inter- and intra-individual variation, sample storage and sampling fraction on human stool microbial community profiles.

Stools are commonly used as proxies for studying human gut microbial communities as sample collection is straightforward, cheap and non-invasive. In large-scale human population surveys, however, sample integrity becomes an issue as it is not logistically feasible for researchers to personally collect stools from every participant. Instead, participants are usually given guidelines on sample packaging and storage, and asked to deliver their stools to a centralised facility. Here, we tested a number of delivery conditions (temperature, duration and addition of preservative medium) and assessed their effects on stool microbial community composition using 16S rRNA gene amplicon sequencing. The largest source of variability in stool community composition was attributable to inter-individual differences regardless of delivery condition. Although the relative effect of delivery condition on community composition was small compared to inter-individual variability (1.6% vs. 60.5%, permutational multivariate analysis of variance [PERMANOVA]) and temporal variation within subjects over 10 weeks (5.2%), shifts in microbial taxa associated with delivery conditions were non-systematic and subject-specific. These findings indicated that it is not possible to model or accurately predict shifts in stool community composition associated with sampling logistics. Based on our findings, we recommend delivery of fresh, preservative-free stool samples to laboratories within 2 hr either at ambient or chilled temperatures to minimise perturbations to microbial community composition. In addition, subsamples from different fractions of the same stool displayed a small (3.3% vs. 72.6% inter-individual variation, PERMANOVA) but significant effect on community composition. Collection of larger sample volumes for homogenisation is recommended.

Hybridization capture reveals microbial diversity missed using current profiling methods.

BACKGROUND: Microorganisms comprise the majority of living organisms on our planet. For many years, exploration of the composition of microbial communities has been performed through the PCR-based study of the small subunit rRNA gene due to its high conservation across the domains of life. The application of this method has resulted in the discovery of many unexpected evolutionary lineages. However, amplicon sequencing is subject to numerous biases, with some taxa being missed, and is limited by the read length of second-generation sequencing platforms, which drastically reduces the phylogenetic resolution. RESULTS: Here, we describe a hybridization capture strategy that allows the enrichment of 16S rRNA genes from metagenomic samples and enables an exhaustive identification and a complete reconstruction of the biomarker. Applying this approach to a microbial mock community and a soil sample, we demonstrated that hybridization capture is able to reveal greater microbial diversity than 16S rDNA amplicon sequencing and shotgun sequencing. The reconstruction of full-length 16S rRNA genes facilitated the improvement of phylogenetic resolution and the discovery of novel prokaryotic taxa. CONCLUSIONS: Our results demonstrate that hybridization capture can lead to major breakthroughs in our understanding of microbial diversity, overcoming the limitations of conventional 16S rRNA gene studies. If applied to a broad range of environmental samples, this innovative approach could reveal the undescribed diversity of the still underexplored microbial communities and could provide a better understanding of ecosystem function.

Accounting for Bacterial Overlap Between Raw Water Communities and Contaminating Sources Improves the Accuracy of Signature-Based Microbial Source Tracking.

Microbial source tracking (MST) analysis is essential to identifying and mitigating the fecal pollution of water resources. The signature-based MST method uses a library of sequences to identify contaminants based on operational taxonomic units (OTUs) that are unique to a certain source. However, no clear guidelines for how to incorporate OTU overlap or natural variation in the raw water bacterial community into MST analyses exist. We investigated how the inclusion of bacterial overlap between sources in the library affects source prediction accuracy. To achieve this, large-scale sampling - including feces from seven species, raw sewage, and raw water samples from water treatment plants - was followed by 16S rRNA amplicon sequencing. The MST library was defined using three settings: (i) no raw water communities represented; (ii) raw water communities selected through clustering analysis; and (iii) local water communities collected across consecutive years. The results suggest that incorporating either the local background or representative bacterial composition improves MST analyses, as the results were positively correlated to measured levels of fecal indicator bacteria and the accuracy at which OTUs were assigned to the correct contamination source increased fourfold. Using the proportion of OTUs with high source origin probability, underpinning a contaminating signal, is a solid foundation in a framework for further deciphering and comparing contaminating signals derived in signature-based MST approaches. In conclusion, incorporating background bacterial composition of water in MST can improve mitigation efforts for minimizing the spread of pathogenic and antibiotic resistant bacteria into essential freshwater resources.

Selection and adaptation of microalgae to growth in 100% unfiltered coal-fired flue gas.

Microalgae have been considered for biological carbon capture and sequestration to offset carbon emissions from fossil fuel combustion. This study shows that mixed biodiverse microalgal communities can be selected for and adapted to tolerate growth in 100% flue gas from an unfiltered coal-fired power plant that contained 11% CO2. The high SOx and NOx emissions required slow adaptation of microalgae over many months, with step-wise increases from 10% to 100% flue gas supplementation and phosphate buffering at higher concentrations. After a rapid decline in biodiversity over the first few months, community profiling revealed Desmodesmus spp. as the dominant microalgae. To the authors' knowledge this work is the first to demonstrate that up 100% unfiltered flue gas from coal-fired power generation can be used for algae cultivation. Implementation of serial passages over a range of photobioreactors may contribute towards the development of microalgal-mediated carbon capture and sequestration processes.

Use of propidium monoazide for selective profiling of viable microbial cells during Gouda cheese ripening.

DNA based microbial community profiling of food samples is confounded by the presence of DNA derived from membrane compromised (dead or injured) cells. Selective amplification of DNA from viable (intact) fraction of the community by propidium monoazide (PMA) treatment could circumvent this problem. Gouda cheese manufacturing is a proper model to evaluate the use of PMA for selective detection of intact cells since large fraction of membrane compromised cells emerges as a background in the cheese matrix during ripening. In this study, the effect of PMA on cheese community profiles was evaluated throughout manufacturing and ripening using quantitative PCR (qPCR). PMA effectively inhibited the amplification of DNA derived from membrane compromised cells and enhanced the analysis of the intact fraction residing in the cheese samples. Furthermore, a two-step protocol, which involves whole genome amplification (WGA) to enrich the DNA not modified with PMA and subsequent sequencing, was developed for the selective metagenome sequencing of viable fraction in the Gouda cheese microbial community. The metagenome profile of PMA treated cheese sample reflected the viable community profile at that time point in the cheese manufacturing.