Bidirectional Enhancement of Nitrogen Removal by Indigenous Synergetic Microalgal-Bacterial Consortia in Harsh Low-C/N Wastewater.

Conventional microalgal-bacterial consortia have limited capacity to treat low-C/N wastewater due to carbon limitation and single nitrogen (N) removal mode. In this work, indigenous synergetic microalgal-bacterial consortia with high N removal performance and bidirectional interaction were successful in treating rare earth tailing wastewaters with low-C/N. Ammonia removal reached 0.89 mg N L-1 h-1, 1.84-fold more efficient than a common microalgal-bacterial system. Metagenomics-based metabolic reconstruction revealed bidirectional microalgal-bacterial interactions. The presence of microalgae increased the abundance of bacterial N-related genes by 1.5- to 57-fold. Similarly, the presence of bacteria increased the abundance of microalgal N assimilation by 2.5- to 15.8-fold. Furthermore, nine bacterial species were isolated, and the bidirectional promotion of N removal by the microalgal-bacterial system was verified. The mechanism of microalgal N assimilation enhanced by indole-3-acetic acid was revealed. In addition, the bidirectional mode of the system ensured the scavenging of toxic byproducts from nitrate metabolism to maintain the stability of the system. Collectively, the bidirectional enhancement system of synergetic microalgae-bacteria was established as an effective N removal strategy to broaden the stable application of this system for the effective treatment of low C/N ratio wastewater.

Resourceful application and mechanism of oyster shell-microalgae synergistic system：Sustainable treatment of harsh low carbon nitrogen ratio actual wastewater.

Microalgal technology holds great promise for both low C/N wastewater treatment and resource recovery simultaneously. Nevertheless, the advancement of microalgal technology is hindered by its reduced nitrogen removal efficiency in low C/N ratio wastewater. In this work, microalgae and waste oyster shells were combined to achieve a total inorganic nitrogen removal efficiency of 93.85% at a rate of 2.05 mg L-1 h-1 in low C/N wastewater. Notably, over four cycles of oyster shell reuse, the reactor achieved an average 85% ammonia nitrogen removal extent, with a wastewater treatment cost of only $0.092/ton. Moreover, microbial community analysis during the reuse of oyster shells revealed the critical importance of timely replacement in inhibiting the growth of non-functional bacteria (Poterioochromonas_malhamensi). The work demonstrated that the oyster shell - microalgae system provides a time- and cost-saving, environmental approach for the resourceful treatment of harsh low C/N wastewater.

BASALT refines binning from metagenomic data and increases resolution of genome-resolved metagenomic analysis.

Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.

A mixed blessing of influent leachate microbes in downstream biotreatment systems of a full-scale landfill leachate treatment plant.

In landfill leachate treatment plants (LLTPs), the microbiome plays a pivotal role in the decomposition of organic compounds, reduction in nutrient levels, and elimination of toxins. However, the effects of microbes in landfill leachate influents on downstream treatment systems remain poorly understood. To address this knowledge gap, we collected 23 metagenomic and 12 metatranscriptomic samples from landfill leachate and activated sludge from various treatment units in a full-scale LLTP. We successfully recovered 1,152 non-redundant metagenome-assembled genomes (MAGs), encompassing a wide taxonomic range, including 48 phyla, 95 classes, 166 orders, 247 families, 238 genera, and 1,152 species. More diverse microbes were observed in the influent leachate than in the downstream biotreatment systems, among which, an unprecedented ∼30 % of microbes with transcriptional expression migrated from the influent to the biological treatment units. Network analysis revealed that 399 shared MAGs across the four units exhibited high node centrality and degree, thus supporting enhanced interactions and increased stability of microbial communities. Functional reconstruction and genome characterization of MAGs indicated that these shared MAGs possessed greater capabilities for carbon, nitrogen, sulfur, and arsenic metabolism compared to non-shared MAGs. We further identified a novel species of Zixibacteria in the leachate influent with discrete lineages from those in other environments that accounted for up to 17 % of the abundance of the shared microbial community and exhibited notable metabolic versatility. Meanwhile, we presented groundbreaking evidence of the involvement of Zixibacteria-encoded genes in the production of harmful gas emissions, such as N2O and H2S, at the transcriptional level, thus suggesting that influent microbes may pose safety risks to downstream treatment systems. In summary, this study revealed the complex impact of the influent microbiome on LLTP and emphasizes the need to consider these microbial characteristics when designing treatment technologies and strategies for landfill leachate management.

A novel culture-enriched metagenomic sequencing strategy effectively guarantee the microbial safety of drinking water by uncovering the low abundance pathogens.

Assessing the presence of waterborne pathogens and antibiotic resistance genes (ARGs) is crucial for managing the environmental quality of drinking water sources. However, detecting low abundance pathogens in such settings is challenging. In this study, a workflow was developed to enrich for broad spectrum pathogens from drinking water samples. A mock community was used to evaluate the effectiveness of various enrichment broths in detecting low-abundance pathogens. Monthly metagenomic surveillance was conducted in a drinking water source from May to September 2021, and water samples were subjected to five enrichment procedures for 6 h to recover the majority of waterborne bacterial pathogens. Oxford Nanopore Technology (ONT) was used for metagenomic sequencing of enriched samples to obtain high-quality pathogen genomes. The results showed that selective enrichment significantly increased the proportions of targeted bacterial pathogens. Compared to direct metagenomic sequencing of untreated water samples, targeted enrichment followed by ONT sequencing significantly improved the detection of waterborne pathogens and the quality of metagenome-assembled genomes (MAGs). Eighty-six high-quality MAGs, including 70 pathogen MAGs, were obtained from ONT sequencing, while only 12 MAGs representing 10 species were obtained from direct metagenomic sequencing of untreated water samples. In addition, ONT sequencing improved the recovery of mobile genetic elements and the accuracy of phylogenetic analysis. This study highlights the urgent need for efficient methodologies to detect and manage microbial risks in drinking water sources. The developed workflow provides a cost-effective approach for environmental management of drinking water sources with microbial risks. The study also uncovered pathogens that were not detected by traditional methods, thereby advancing microbial risk management of drinking water sources.

Salinity-triggered homogeneous selection constrains the microbial function and stability in lakes.

Climate change and anthropogenic exploitation have led to the gradual salinization of inland waters worldwide. However, the impacts of this process on the prokaryotic plankton communities and their role in biogeochemical cycles in the inland lake are poorly known. Here, we take a space-for-time substitution approach, using 16S rRNA gene amplicon sequencing and metagenomic sequencing. We analyzed the prokaryotic plankton communities of 11 lakes in northwest China, with average water salinities ranging from 0.002 to 14.370%. The results demonstrated that, among the various environmental parameters, salinity was the most important driver of prokaryotic plankton ß-diversity (Mantel test, r = 0.53, P < 0.001). (1) Under low salinity, prokaryotic planktons were assembled by stochastic processes and employed diverse halotolerant strategies, including the synthesis and uptake of compatible solutes and extrusion of Na+ or Li+ in exchange for H+. Under elevated salinity pressure, strong homogeneous selection meant that only planktonic prokaryotes showing an energetically favorable halotolerant strategy employing an Mnh-type Na+/H+ antiporter remained. (2) The decreasing taxonomic diversity caused by intense environmental filtering in high-salinity lakes impaired functional diversity related to substance metabolism. The prokaryotes enhanced the TCA cycle, carbon fixation, and low-energy-consumption amino acid biosynthesis in high-salinity lakes. (3) Elevated salinity pressure decreased the negative:positive cohesion and the modularity of the molecular ecology networks for the planktonic prokaryotes, indicating a precarious microbial network. Our findings provide new insights into plankton ecology and are helpful for the protecting of the biodiversity and function of inland lakes against the background of salinization. KEY POINTS: • Increased salinity enhances homogeneous selection in the microbial assembly. • Elevated salinity decreases the microbial co-occurrence networks stability. • High salinity damages the microbial function diversity.

High Sensitivity, Wide Linear-Range Strain Sensor Based on MXene/AgNW Composite Film with Hierarchical Microcrack.

Stretchable strain sensors suffer the trade-off between sensitivity and linear sensing range. Developing sensors with both high sensitivity and wide linear range remains a formidable challenge. Different from conventional methods that rely on the structure design of sensing nanomaterial or substrate, here a heterogeneous-surface strategy for silver nanowires (AgNWs) and MXene is proposed to construct a hierarchical microcrack (HMC) strain sensor. The heterogeneous surface with distinct differences in cracks and adhesion strengths divides the sensor into two regions. One region contributes to high sensitivity through penetrating microcracks of the AgNW/MXene composite film during stretching. The other region maintains conductive percolation pathways to provide a wide linear sensing range through network microcracks. As a result, the HMC sensor exhibits ultrahigh sensitivity (gauge factor ≈ 244), broad linear range (ɛ = 60%, R2 ≈ 99.25%), and fast response time (<30 ms). These merits are confirmed in the detection of large and subtle human motions and digital joint movement for Morse coding. The manipulation of cracks on the heterogeneous surface provides a new paradigm for designing high-performance stretchable strain sensors.

Effective-compound combination of Bufei Yishen formula III combined with ER suppress airway mucus hypersecretion in COPD rats: via EGFR/MAPK signaling.

BACKGROUND: The aim of this study was to explore the combined efficacy ofeffective-component compatibility of Bufei Yishen formula III (ECC-BYF III) and exercise rehabilitation (ER) in inhibiting airway mucus hypersecretion in a chronic obstructive pulmonary disease (COPD) rat model. METHODS: A total of 48 SD rats were divided into control, model, acetylcysteine (NAC), ECC-BYF III, ER, and ECC-BYF III + ER groups (n=8). COPD rats were exposed to cigarette smoke and bacteria for 8 weeks and administered various treatments over the next eight weeks. Rats were euthanized at week 17 after pulmonary function testing. Pathological examination of lung tissues was performed. IL-6 and IL-10 levels were measured in bronchoalveolar lavage fluid (BALF) and protein levels of MUC5AC, MUC5B, AQP-5, EGFR, ERK, JNK, and p38 were measured in lung tissues. RESULTS: Improved pulmonary function and pathological changes were observed in ECC-BYF III, ECC-BYF III + ER, and NAC groups. ECC-BYF III and ECC-BYF III + ER had greater mean alveolar number (MAN) compared with NAC. Lung inflammation and goblet cell generation were reduced and MUC5AC, MUC5B and AQP-5 expressions were lower in all treatment groups. ECC-BYF III has more significant effect on MUC5AC than ER and NAC. ECC-BYFIII + ER had a greater effect on suppressing IL-6 in BALF compared with other treatments. ECC-BYFIII, ER, and ECC-BYF III + ER reduced EGFR, ERK, JNK, and p38 phosphorylated protein levels. ECC-BYFIII+ER had a greater effect on p-JNK and p-p38 than ECC-BYFIII and NAC. CONCLUSION: ECC-BYF III, ER, and ECC-BYF III + ER have efficacy in inhibiting airway mucus hypersecretion with improved pulmonary function and pathological changes. ECC-BYF III had a greater effect in improving MAN and MUC5AC in lung tissue. ECC-BYF III+ER had a greater effect in alleviating pulmonary pathology and inflammation. These effects may be mediated by inhibition of the EGFR/MAPK pathway.

Development of quantitative wastewater surveillance models facilitated the precise epidemic management of COVID-19.

Wastewater surveillance serves as a promising approach to elucidate the silent transmission of SARS-CoV-2 in communities. To understand the decay of the coronavirus in sewage pipes, the decay of the coronavirus traveling over 20 km distance of pipeline was analyzed. Based on the decay model, a WWTP and a community model were then proposed for predicting COVID-19 cases in Xi'an and Nanchang city during the COVID-19 outbreak in 2021 and 2022. The results suggested that Monte Carol simulations estimated 23.3, 50.1, 127.3 and 524.2 infected persons in the Yanta district of Xi'an city on December 14th, 18th, 22nd and 26th of 2021, respectively, which is largely consistent with the clinical reports. Next, we further conducted wastewater surveillance in two WWTPs that covered the whole metropolitan region in Nanchang to validate the robustness of the WWTP model from December 2021 to April 2022. SARS-CoV-2 signals were detected in two WWTPs from March 15th to April 5th. Predicted infection numbers were in agreement with the actual infection cases, which promoted precise epidemic control. Finally, community wastewater surveillance was conducted for 40 communities that were not 100 % covered by massive nucleic acid testing in Nanchang city, which accurately identified the SARS-CoV-2 carriers not detected by massive nucleic acid testing. In conclusion, accurate prediction of COVID-19 cases based on WWTP and community models promoted precise epidemic control. This work highlights the viability of wastewater surveillance for outbreak evaluation and identification of hidden cases, which provides an extraordinary example for implementing precise epidemic control of COVID-19.

Metagenomic sequencing combined with flow cytometry facilitated a novel microbial risk assessment framework for bacterial pathogens in municipal wastewater without cultivation.

A workflow that combined metagenomic sequencing with flow cytometry was developed. The absolute abundance of pathogens was accurately estimated in mock communities and real samples. Metagenome-assembled genomes binned from metagenomic data set is robust in phylogenetic analysis and virulence profiling.

Response of the plant core microbiome to Fusarium oxysporum infection and identification of the pathobiome.

Plant core microbiomes consist of persistent key members that provide critical host functions, but their assemblages can be interrupted by biotic and abiotic stresses. The pathobiome is comprised of dynamic microbial interactions in response to disease status of the host. Hence, identifying variation in the core microbiome and pathobiome can significantly advance our understanding of microbial-microbial interactions and consequences for disease progression and host functions. In this study, we combined glasshouse and field studies to analyse the soil and plant rhizosphere microbiome of cotton plants (Gossypium hirsutum) in the presence of a cotton-specific fungal pathogen, Fusarium oxysporum f. sp. vasinfectum (FOV). We found that FOV directly and consistently altered the rhizosphere microbiome, but the biocontrol agents enabled microbial assemblages to resist pathogenic stress. Using co-occurrence network analysis of the core microbiome, we identified the pathobiome comprised of the pathogen and key associate phylotypes in the cotton microbiome. Isolation and application of some negatively correlated pathobiome members provided protection against plant infection. Importantly, our field survey from multiple cotton fields validated the pattern and responses of core microbiomes under FOV infection. This study advances key understanding of core microbiome responses and existence of plant pathobiomes, which provides a novel framework to better manage plant diseases in agriculture and natural settings.

Biofertilizers can enhance nitrogen use efficiency of sugarcane.

Fertilizers are costly inputs into crop systems. To compensate for inefficiencies and losses from soil, farmers apply on average double the amount of nitrogen (N) fertilizer acquired by crops. We explored if N efficiency improves with biofertilizers formulated with organic waste, mineral N or plant growth-promoting rhizobacteria (PGPR). We compared treatments receiving mineral N fertilizer or biofertilizers at industry-recommended (100%) or lower (60%) N rates at two commercial sugarcane farms. Biofertilizer at the 60% N-rate generated promising results at one farm with significantly higher biomass and sugar yield than the no-N control, which matched the 100% mineral N treatment. This yield difference was accompanied by a shift in microbial diversity and composition. Correlation analysis confirmed that shifts in microbial communities were strongly linked to soil mineral N levels, as well as crop productivity and yield. Microbial co-occurrence networks further revealed that biofertilizer, including treatments with an added PGPR, can enhance bacterial associations, especially in the context of complex fungal networks. Collectively, the results confirm that biofertilizers have quantifiable effects on soil microbial communities in a crop system setting, which underscores the opportunities for biofertilizers to promote N use efficiency and the circular N economy.

A flexible and stretchable bionic true random number generator.

The volume of securely encrypted data transmission increases continuously in modern society with all things connected. Towards this end, true random numbers generated from physical sources are highly required for guaranteeing security of encryption and decryption schemes for exchanging sensitive information. However, majority of true random number generators (TRNGs) are mechanically rigid, and thus cannot be compatibly integrated with some specific flexible platforms. Herein, we present a flexible and stretchable bionic TRNG inspired by the uniqueness and randomness of biological architectures. The flexible TRNG film is molded from the surface microstructures of natural plants (e.g., ginkgo leaf) via a simple, low-cost, and environmentally friendly manufacturing process. In our proof-of-principle experiment, the TRNG exhibits a fast generation speed of up to 1.04 Gbit/s, in which random numbers are fully extracted from laser speckle patterns with a high extraction rate of 72%. Significantly, the resulting random bit streams successfully pass all randomness test suites including NIST, TestU01, and DIEHARDER. Even after 10,000 times cyclic stretching or bending tests, or during temperature shock (-25-80 °C), the bionic TRNG still reveals robust mechanical reliability and thermal stability. Such a flexible TRNG shows a promising potential in information security of emerging flexible networked electronics. Electronic Supplementary Material: Supplementary material (light path diagram of transmitted laser speckle, pseudo random pattern, statistical distribution of bionic microstructures, haze of the bionic TRNG film, multi-layer circular laser intensity pattern, percentage of bit 0/1 for different hashed images, Pearson correlation coefficient between 100 different speckle images, the whole process of randomness extraction, SEM images of the flexible TRNG film after 10,000 times stretching and bending, continuous work stability of the TRNG at low or high temperature, light path diagram of reflective laser speckle, and detailed randomness test results of NIST, TestU01, and DIEHARDER) is available in the online version of this article at 10.1007/s12274-022-4109-9.

Genome-centric metagenomics provides new insights into the microbial community and metabolic potential of landfill leachate microbiota.

Landfills are important sources of microorganisms associated with anaerobic digestion. However, the knowledge on microbiota along with their functional potential in this special habitat are still lacking. In this study, we recovered 1168 non-redundant metagenome-assembled genomes (MAGs) from nine landfill leachate samples collected from eight cities across China, spanning 42 phyla, 73 classes, 114 orders, 189 families, and 267 genera. Totally, 74.1% of 1168 MAGs could not be classified to any known species and 5.9% of these MAGs belonged to microbial dark matter phyla. Two putative novel classes were discovered from landfill leachate samples. The identification of thousands of novel carbohydrate-active enzymes showed similar richness level compared to the cow rumen microbiota. The methylotrophic methanogenic pathway was speculated to contribute significantly to methane production in the landfill leachate because of its co-occurrence with the acetoclastic and hydrogenotrophic methanogenic pathways. The genetic potential of dissimilatory nitrate reduction to ammonium (DNRA) was observed, implying DNRA may play a role in ammonium generation in landfill leachate. These findings implied that landfill leachate might be a valuable microbial resource repository and filled the previous understanding gaps for both methanogenesis and nitrogen cycling in landfill leachate microbiota. Our study provides a comprehensive genomic catalog and substantially provides unprecedented taxonomic and functional profiles of the landfill leachate microbiota.

Metagenomics combined with comprehensive validation as a public health risk assessment tool for urban and agricultural run-off.

Early detection of emerging and life-threatening pathogens circulating in complex environments is urgently required to combat infectious diseases. This study proposed a public health risk assessment workflow with three stages, pathogen screening, pathogen genotyping, and risk assessment. In stage one, pathogens were screened with metagenomic sequencing, microfluidic chip, and qPCR. In stage two, pathogens were isolated and genotyped with multi-locus sequence typing (MLST) or conventional PCR. Finally, virulence genes from metagenomic data were assessed for pathogenicity. Two regions (Donggang and Zhanjiang) with potential public health concerns were selected for evaluation, each of which comprised of one urban and one farming wastewater sampling location. Overall, metagenomic sequencing reflected the variation in the relative abundance of medically important bacteria. Over 90 bacterial pathogens were monitored in the metagenomic dataset, of which 56 species harbored virulence genes. In Donggang, a pathogenic Acinetobacter sp. reached high abundances in 2018 and 2020, whereas all pathogenic Vibrio spp. peaked in October 2019. In Zhanjiang, A. baumanni, and other Enterobacteriaceae species were abundantly present in 2019 and 2020, whereas Aeromonas and Vibrio spp. peaked in November-2017. Forty species were subsequently isolated and subtyped by MLST, half of which were prevalent genotypes in clinical data. Additionally, we identified the African Swine Fever Virus (ASFV) in water samples collected in 2017, ahead of the first reported ASFV outbreak in 2018 in China. RNA viruses like Hepatitis A virus (HAV) and Enterovirus 71 (EV71) were also detected, with concentrations peaking in April 2020 and April 2018, respectively. The dynamics of HAV and EV71 were consistent with local epidemic trends. Finally, based on the virulence gene profiles, our study identified the risk level in wastewater of two cities. This workflow illustrates the potential for an early warning of local epidemics, which helps to prioritize the preparedness for specific pathogens locally.

Stretchable Transparent Electrode via Wettability Self-Assembly in Mechanically Induced Self-Cracking.

Stretchable and transparent electrodes (STEs) are indispensable components in numerous emerging applications such as optoelectrical devices and wearable devices used in health monitoring, human-machine interaction, and artificial intelligence. However, STEs have limitations in conductivity, robustness, and transmittance owing to the exposure of the substrate and fatigue deformation of nanomaterials under strain. In this study, an STE consisting of conductive materials embedded in in situ self-cracking strain-spread channels by wettability self-assembly is fabricated. Finite element analysis is used to simulate the crevice growth using the representative unit cell network and strain deformation using a random network. The embedded conductive materials are partly protected by the strain-opening crevice channel, and network dissociation is avoided under stretching, showing a maximum strain of 125%, a transmittance of approximately 89.66% (excluding the substrate) with a square resistance of 9.8 Ω sq-1, and high stability in an environment with high temperature and moisture. The wettability self-assembly coating process is verified and expanded to several kinds of hydrophilic inks and hydrophobic coating materials. The fabricated STE can be employed as a strain sensor in motion sensing, vital sign and posture feedback, and mimicking bioelectronic spiderweb with spatial gravity induction.

Specific Denitrifying and Dissimilatory Nitrate Reduction to Ammonium Bacteria Assisted the Recovery of Anammox Community From Nitrite Inhibition.

The anaerobic ammonium oxidation (anammox) by autotrophic anaerobic ammonia-oxidizing bacteria (AnAOB) is a biological process used to remove reactive nitrogen from wastewater. It has been repeatedly reported that elevated nitrite concentrations can severely inhibit the growth of AnAOB, which renders the anammox process challenging for industrial-scale applications. Both denitrifying (DN) and dissimilatory nitrate reduction to ammonium (DNRA) bacteria can potentially consume excess nitrite in an anammox system to prevent its inhibitory effect on AnAOB. However, metabolic interactions among DN, DNRA, and AnAOB bacteria under elevated nitrite conditions remain to be elucidated at metabolic resolutions. In this study, a laboratory-scale anammox bioreactor was used to conduct an investigation of the microbial shift and functional interactions of AnAOB, DN, and DNRA bacteria during a long-term nitrite inhibition to eventual self-recovery episode. The relative abundance of AnAOB first decreased due to high nitrite concentration, which lowered the system's nitrogen removal efficiency, but then recovered automatically without any external interference. Based on the relative abundance variations of genomes in the inhibition, adaptation, and recovery periods, we found that DN and DNRA bacteria could be divided into three niche groups: type I (types Ia and Ib) that includes mainly DN bacteria and type II and type III that include primarily DNRA bacteria. Type Ia and type II bacteria outcompeted other bacteria in the inhibition and adaptation periods, respectively. They were recognized as potential nitrite scavengers at high nitrite concentrations, contributing to stabilizing the nitrite concentration and the eventual recovery of the anammox system. These findings shed light on the potential engineering solutions to maintain a robust and efficient industrial-scale anammox process.

Distinct Microbiota Dysbiosis in Patients with Non-Erosive Reflux Disease and Esophageal Adenocarcinoma.

Non-erosive reflux disease (NERD) and esophageal adenocarcinoma (EAC) are often regarded as bookends in the gastroesophageal reflux disease spectrum. However, there is limited clinical evidence to support this disease paradigm while the underlying mechanisms of disease progression remain unclear. In this study, we used 16S rRNA sequencing and mass-spectrometer-based proteomics to characterize the esophageal microbiota and host mucosa proteome, respectively. A total of 70 participants from four patient groups (NERD, reflux esophagitis, Barrett's esophagus, and EAC) and a control group were analyzed. Our results showed a unique NERD microbiota composition, distinct to control and other groups. We speculate that an increase in sulfate-reducing Proteobacteria and Bacteroidetes along with hydrogen producer Dorea are associated with a mechanistic role in visceral hypersensitivity. We also observed a distinct EAC microbiota consisting of a high abundance of lactic acid-producing bacteria (Staphylococcus, Lactobacillus, Bifidobacterium, and Streptococcus), which may contribute towards carcinogenesis through dysregulated lactate metabolism. This study suggests the close relationship between esophageal mucosal microbiota and the appearance of pathologies of this organ.

Plant Microbiomes: Do Different Preservation Approaches and Primer Sets Alter Our Capacity to Assess Microbial Diversity and Community Composition?

The microbial communities associated with plants (the plant microbiome) play critical roles in regulating plant health and productivity. Because of this, in recent years, there have been significant increase in studies targeting the plant microbiome. Amplicon sequencing is widely used to investigate the plant microbiome and to develop sustainable microbial agricultural tools. However, performing large microbiome surveys at the regional and global scales pose several logistic challenges. One of these challenges is related with the preservation of plant materials for sequencing aiming to maintain the integrity of the original diversity and community composition of the plant microbiome. Another significant challenge involves the existence of multiple primer sets used in amplicon sequencing that, especially for bacterial communities, hampers the comparability of datasets across studies. Here, we aimed to examine the effect of different preservation approaches (snap freezing, fresh and kept on ice, and air drying) on the bacterial and fungal diversity and community composition on plant leaves, stems and roots from seven plant species from contrasting functional groups (e.g. C3, C4, N-Fixers, etc.). Another major challenge comes when comparing plant to soil microbiomes, as different primers sets are often used for plant vs. soil microbiomes. Thus, we also investigated if widely used 16S rRNA primer set (779F/1193R) for plant microbiome studies provides comparable data to those often used for soil microbiomes (341F/805R) using 86 soil samples. We found that the community composition and diversity of bacteria or fungi were robust to contrasting preservation methods. The primer sets often used for plants provided similar results to those often used for soil studies suggesting that simultaneous studies on plant and soil microbiomes are possible. Our findings provide novel evidence that preservation approaches do not significantly impact plant microbiome data interpretation and primer differences do not impact the treatment effect, which has significant implication for future large-scale and global surveys of plant microbiomes.

Microbiome-Mediated Stress Resistance in Plants.

Plants are subjected to diverse biotic and abiotic stresses in life. These can induce changes in transcriptomics and metabolomics, resulting in changes to root and leaf exudates and, in turn, altering the plant-associated microbial community. Emerging evidence demonstrates that changes, especially the increased abundance of commensal microbes following stresses, can be beneficial for plant survival and act as a legacy, enhancing offspring fitness. However, outstanding questions remain regarding the microbial role in plant defense, many of which may now be answered utilizing a novel synthetic community approach. In this article, building on our current understanding on stress-induced changes in plant microbiomes, we propose a 'DefenseBiome' concept that informs the design and construction of beneficial microbial synthetic communities for improving fundamental understanding of plant-microbial interactions and the development of plant probiotics.