AbstractMeasles is a contagious, vaccine-preventable viral disease that can be shed into wastewater by infected individuals. In September 2025, as part of an ongoing, nontargeted, ultra-deep metagenomic sequencing effort of wastewater in Cook County, Illinois, we detected measles reads from a facility serving more than 1 million people. Out of more than 900 million reads sequenced from wastewater collected on September 14, 2025, 43 matched measles virus genotype B3. Subsequent genomic analysis linked these reads to a confirmed measles infection that was present in the community on that day, demonstrating that untargeted metagenomics appeared to detect a single measles infection in a large municipal wastewater stream.

The Bacterial and Viral Bioinformatics Resource Center (BV-BRC; https://www.bv-brc.org) is a comprehensive resource supporting research on bacterial and viral pathogens. It currently hosts over 14 million publicly available genomes and 33 high-throughput bioinformatic analysis services with numerous visual analytic tools allowing researchers to analyze their private data, generate comparisons with public data, and share data and results with colleagues. In recent years, the BV-BRC has added several new analysis services to support rapid comparative genomics and epidemiological analysis, viral genome assembly and annotation, viral subspecies classification, wastewater analysis, and molecular docking. In addition, several existing services have been updated to incorporate state-of-the-art tools, including assembly, annotation, taxonomic classification, metagenomic read mapping, and RNA-seq analysis. A new tool, called BV-BRC Copilot, provides an AI-powered natural-language interface that combines large language models with retrieval-augmented generation to guide users through data exploration, analysis workflows, and knowledge integration. With expanded outbreak tracking pages, training and educator engagement, and continued development of novel AI-driven analytics, BV-BRC continues to provide a unified resource to meet the evolving needs of the global research community.

Wastewater surveillance of respiratory pathogens can provide timely estimates of viral activity and disease trends in a population. Indoor air surveillance could be used similarly with some advantages but remains largely unvalidated at the community-scale. Here, an indoor air surveillance program was employed as part of public health environmental surveillance in Chicago, Illinois, USA. Ten air samplers were placed in healthcare and congregate living settings across the city. Weekly air samples were evaluated for influenza A, influenza B, respiratory syncytial virus, and SARS-CoV-2 over two respiratory virus seasons (2023-2025). Citywide, aggregated air sample positivity and viral load were closely correlated with local clinical case and wastewater surveillance data across all respiratory viruses. Virus trends in air data often preceded clinical and wastewater, although this varied across pathogens and respiratory virus seasons. Further, whole-genome sequencing of SARS-CoV-2 showed close correlation of variant proportions across all datasets. At the building-scale, air samples obtained from a single sampling device provided efficient respiratory virus surveillance, with respiratory pathogen levels mirroring citywide clinical surveillance data. These data demonstrate that air surveillance can provide respiratory virus case and variant trend data at a building or community-scale, serving as an alternative or complementary tool for public health environmental surveillance.

Wastewater testing has emerged as an effective tool for monitoring levels of SARS-CoV-2 infection in sewered communities. As of July 2024, PCR-based methods continue to be the most widely used methods in wastewater surveillance. Data from PCR-based wastewater testing is usually available to public health authorities in near real time, typically within 5 to 7 days after waste enters the sewer. Unfortunately, while these methods can accurately detect and quantify SARS-CoV-2, they are not usually used to differentiate between the multitude of variants, including variants that are classified as Variants of High Consequence (VOHC) and Variants of Concern (VOC). Currently, to identify these variants, the extracted nucleic acids must be analyzed using resource-intensive sequencing-based methods. Moreover, not every lab has access to sequencing technology, so availability of equipment and expertise is also a roadblock besides These costly and time-consuming sequencing methods, while informative, diminish some of the early warning benefits provided by wastewater surveillance. Moreover, not every lab has access to sequencing technology, creating additional barriers due to the availability of equipment and expertise. In response to these analytical shortcomings, we developed and assessed an alternative approach for variant monitoring in wastewater using customizable dPCR-based genotyping assays. This approach is an expansion from a previously described method for analyzing clinical samples utilizing customizable qPCR-based genotyping. Relative to sequencing, this approach is cost-effective, fast, and easily implemented. We combined the dPCR-based wastewater genotyping approach along with the well-established Nanotrap® Particles virus concentration method as part of a wastewater processing protocol to perform SARS-CoV-2 genotyping in five wastewater testing labs across multiple regions in the United States. The results for the wastewater genotyping approach are displayed on a public-facing dashboard alongside clinical genotyping results and GISAID data (see https://tracker.rosalind.bio). Despite conducting genotyping on fewer wastewater samples than clinical samples, our approach effectively detected signals of emerging variants and trends in SARS-CoV-2 variants within the community, similar to clinical analyses. For instance, in Georgia, the rapid rise and dominance of the Unknown and BA.2.86\*/JN\* variants in early 2024 were consistently observed in wastewater samples and closely matched trends in the GISAID clinical sequencing database. Similarly, the EG.5* and FL* variants showed elevated signals in wastewater before clinical detection, highlighting the early warning potential of wastewater testing. Detailed analysis of multiple datasets from various states revealed consistency in the rise and fall of variants across wastewater genotyping, clinical genotyping, and GISAID data. This consistency demonstrates that the prevalence of variants in wastewater closely matches that in clinical settings, underscoring the capability of wastewater-based surveillance to provide extended monitoring of circulating variants, often preceding clinical detections by several weeks. We further assessed the wastewater genotyping approach by calculating positive percent agreement for detection of four variants (JN, EG.5, FL, and XBB) between the genotyping results and whole genome sequencing results for a set of 129 matched samples that were analyzed using both methods. The agreement ranged between 54% agreement for FL to 97% agreement for JN, with an average of 76% agreement across all samples for all four variants. Additionally, we estimate that collecting and analyzing data using the dPCR genotyping method is significantly less expensive and time-consuming compared to next-generation sequencing. Labs that outsource next-generation sequencing face much higher costs and longer delays. Transitioning to multiplex dPCR for variant detection could further reduce both cost and turnaround time. Finally, we discuss the challenges and lessons learned in the development, validation, and implementation of dPCR-based wastewater genotyping. These findings support the use of wastewater-based surveillance as a complementary approach to clinical surveillance, offering a broader and more inclusive picture of variant prevalence and transmission in the community. ### Competing Interest Statement Patrick Acer, Patrick Andersen, Robbie Barbero, Stephanie Barksdale, Sophia Bellakbira, Dalton Bunde, Ross Dunlap, James Erickson, Daniel Goldfarb, Tara Jones-Roe, Michael Kilroy, Hien Le, Ben Lepene, Emily Milich, Ayan Mohamed, Sayed Mosavi, Denton Munns, Jared Obermeyer, Anurag Patnaik, Ganit Pricer, Marion Reven, Dalaun Richardson, Chamodya Ruhunusiri, Sahoo Saswata, Lauren P. Saunders, Olivia Swahn, Kalpita Vengurlekar, and David White are employees of Ceres Nanosciences. Jean Lozach, Aouda Patricia Flores-Baffi, Fletcher Easton, Maya Dahlke, Andrea Fang, David Cibin, and Tim Wesselman are employees of Rosalind, Inc. Dr. Sarah Kane, Jim Huang, Johannah Gillespie, and Andrew Jones are employees of GT Molecular. ### Funding Statement This project has been funded in part by the NIH Rapid Acceleration of Diagnostics (RADxSM) initiative with federal funds from the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health. The current contract is funded from the Public Health and Social Services Emergency Fund through the Biomedical Advanced Research and Development Authority, HHS Office of the Assistant Secretary for Preparedness and Response, Department of Health and Human Services, under Contract No. 75N92021C00012. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All clinical samples, retrospective and prospective, were collected predominantly in the states of Washington, Florida, and California. Aegis Sciences Corporation, Helix OpCo, and University of Washington are Clinical Laboratory Improvement Amendments (CLIA) certified labs participating in the CDC National SARSCoV2 Strain Surveillance sequencing program to monitor variant distribution in the US. The Pearl independent institutional review board (IRB) gave ethical approval for the use of Aegis Sciences Corporation de identified remnants of clinical testing. Western Institutional Review Board Copernicus Group, the institutional review board of record for the Helix Respiratory Registry, gave ethical approval for the use of Helix OpCo de-identified remnants of clinical testing. Use of the University of Washington de identified excess clinical specimens was approved with a consent waiver by the University of Washington IRB. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380-1800 mL) collected at depths of 0-2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

As COVID-19 becomes endemic, public health departments benefit from improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging due to the high noise typical of environmental samples. We have developed a generalized pipeline using in- and out-of-sample model selection to test the ability of different correction models to reduce the variance in wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but the pipeline should be used to reevaluate any new data set as the sources of variance may change across locations, lab methods, and disease states. Using our best-fit model, we investigated the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We did this in a rolling manner for corrected wastewater data and for other prevalence indicators and statistically compared the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We found that wastewater trends often lead other COVID-19 indicators in predicting new surges.

Wastewater testing can inform public health action as a component of polio outbreak response. During 2022-2023, a total of 7 US jurisdictions (5 states and 2 cities) participated in prospective or retrospective testing of wastewater for poliovirus after a paralytic polio case was identified in New York state. Two distinct vaccine-derived poliovirus type 2 viruses were detected in wastewater from New York state and New York City during 2022, representing 2 separate importation events. Of those viruses, 1 resulted in persistent community transmission in multiple New York counties and 1 paralytic case. No poliovirus was detected in the other participating jurisdictions (Connecticut, New Jersey, Michigan, and Illinois and Chicago, IL). The value of routine wastewater surveillance for poliovirus apart from an outbreak is unclear. However, these results highlight the ongoing risk for poliovirus importations into the United States and the need to identify undervaccinated communities and increase vaccination coverage to prevent paralytic polio.

Wastewater SARS-CoV-2 surveillance has been deployed since the beginning of the COVID-19 pandemic to monitor the dynamics in virus burden in local communities. Genomic surveillance of SARS-CoV-2 in wastewater, particularly efforts aimed at whole genome sequencing for variant tracking and identification, are still challenging due to low target concentration, complex microbial and chemical background, and lack of robust nucleic acid recovery experimental procedures. The intrinsic sample limitations are inherent to wastewater and are thus unavoidable. Here, we use a statistical approach that couples correlation analyses to a random forest-based machine learning algorithm to evaluate potentially important factors associated with wastewater SARS-CoV-2 whole genome amplicon sequencing outcomes, with a specific focus on the breadth of genome coverage. We collected 182 composite and grab wastewater samples from the Chicago area between November 2020 to October 2021. Samples were processed using a mixture of processing methods reflecting different homogenization intensities (HA + Zymo beads, HA + glass beads, and Nanotrap), and were sequenced using one of the two library preparation kits (the Illumina COVIDseq kit and the QIAseq DIRECT kit). Technical factors evaluated using statistical and machine learning approaches include sample types, certain sample intrinsic features, and processing and sequencing methods. The results suggested that sample processing methods could be a predominant factor affecting sequencing outcomes, and library preparation kits was considered a minor factor. A synthetic SARS-CoV-2 RNA spike-in experiment was performed to validate the impact from processing methods and suggested that the intensity of the processing methods could lead to different RNA fragmentation patterns, which could also explain the observed inconsistency between qPCR quantification and sequencing outcomes. Overall, extra attention should be paid to wastewater sample processing (i.e., concentration and homogenization) for sufficient and good quality SARS-CoV-2 RNA for downstream sequencing.

Several pyridine derivatives including the pesticide nitrapyrin [2-chloro-6-(trichloromethyl) pyridine] are strong inhibitors of methane monooxygenase, a key enzyme of aerobic methane (CH 4 ) oxidation. In this study we examined the effects of 2-chloro-6-methylpyridine (2C6MP) concentration on aerobic CH 4 oxidation and the development of populations of putative methanotrophs in sediment from Old Woman Creek, a freshwater estuary in Huron Co., Ohio. Experimental systems were prepared in serum bottles containing minimal medium with a headspace containing 20% O 2 and 10% CH 4 . The microcosms were spiked with 2C6MP to achieve concentrations of 0, 0.1, 1, or 10 mM and inoculated with sediment. When headspace CH 4 concentrations decreased from 10% to < 2%, subsamples were taken for DNA extraction and sequencing of 16S rRNA gene amplicons. There was minimal effect of 2C6MP on CH 4 oxidation at concentrations of 0.1, and 1 mM, but complete inhibition for > 20 months was observed at 10 mM. ANOSIM of weighted UniFrac distances between groups of triplicate samples supported a primary distinction of the inoculum relative to the enrichments (R=0.999) and a secondary distinction between bottles containing 2C6MP versus those without (R=0.464 [0.1 mM]; R=0.894 [1 mM]). The inoculum was dominated by members of the Proteobacteria (49.9±1.5%), and to a lesser extent by Bacteroidetes (8.8±0.2%), Acidobacteria (8.9±0.4%), and Verrucomicrobia (4.4±0.3%). In enrichments with or without 2C6MP, Proteobacteria expanded to comprise 65–70% of the total. In the absence of inhibitor, members of the Methylococcaceae and Methylophilaceae increased in relative abundance from < 0.1% of the inoculum to 8.5±1.0% and 13.4±2.3%, of the total community respectively. At both 0.1 and 1 mM concentrations of the inhibitor, the Methylococcaceae were much less abundant, representing 3.3±0.5% and 2.8±3.3% respectively. No inhibition of the Methylophilaceae was seen at the lower concentration of 2C6MP, but at the higher concentration this taxon was only 7.8±1.1% of the total. In contrast, members of the Crenotrichaceae , another group of methane oxidizers, increased in relative abundance with greater amounts of inhibitor, representing 8.6±3.6% of the total at 0.1 mM and 12.0±4.5% at 1 mM, compared to only 4.1±0.4% when no inhibitor was present. These results clearly show changes in the populations of putative aerobic methanotrophs relative to the amount of 2C6MP present.

Cervical microbiota (CM) are considered an important factor affecting the progression of cervical intraepithelial neoplasia (CIN) and are implicated in the persistence of human papillomavirus (HPV). Collection of liquid-based cytology (LBC) samples is routine for cervical cancer screening and HPV genotyping and can be used for long-term cytological biobanking. We sought to determine whether it is possible to access microbial DNA from LBC specimens, and compared the performance of four different extraction protocols: (ZymoBIOMICS DNA Miniprep Kit; QIAamp PowerFecal Pro DNA Kit; QIAamp DNA Mini Kit; and IndiSpin Pathogen Kit) and their ability to capture the diversity of CM from LBC specimens. LBC specimens from 20 patients (stored for 716 ± 105 days) with CIN values of 2 or 3 were each aliquoted for each of the four kits. Loss of microbial diversity due to long-term LBC storage could not be assessed due to lack of fresh LBC samples. Comparisons with other types of cervical sampling were not performed. We observed that all DNA extraction kits provided equivalent accessibility to the cervical microbial DNA within stored LBC samples. Approximately 80% microbial genera were shared among all DNA extraction protocols. Potential kit contaminants were observed as well. Variation between individuals was a significantly greater influence on the observed microbial composition than was the method of DNA extraction. We also observed that HPV16 was significantly associated with community types that were not dominated by Lactobacillus iners .

Methane is a microbially derived greenhouse gas whose emissions are highly variable throughout wetland ecosystems. Differences in plant community composition account for some of this variability, suggesting an influence of plant species on microbial community structure and function in these ecosystems. Given that closely related plant species have similar morphological and biochemical features, we hypothesize that plant evolutionary history is related to differences in microbial community composition. To examine species-specific patterns in microbiomes, we selected five monoculture-forming wetland plant species based on the evolutionary distances among them. We detected significant differences in microbial communities between sample types (unvegetated soil, bulk soil, rhizosphere soil, internal root tissues, and internal leaf tissues) associated with these plant species based on 16S relative abundances. We additionally found that differences in plant evolutionary history were correlated with variation in microbial communities across plant species within each sample type. Using qPCR, we observed substantial differences in overall methanogen and methanotroph population sizes between plant species and sample types. Methanogens tended to be most abundant in rhizosphere soils while methanotrophs were the most abundant in roots. Given that microbes influence methane flux and that plants affect methanogen and methanotroph populations, plant species contribute to variable degrees of methane emissions. Incorporating the influence of plant evolutionary history into future modeling efforts may improve predictions of wetland methane emission since microbial community differences correlate with differences in plant evolutionary history.

Efforts to study the microbial communities associated with corals can be limited by inefficiencies in the sequencing process due to high levels of host amplification by universal bacterial 16S rRNA gene primers. Here, we develop an inexpensive peptide nucleic acid (PNA) clamp that binds to a target sequence of host DNA during PCR and blocks amplification. We then test the ability of this PNA clamp to mitigate host contamination and increase overall microbial sequence coverage on samples from three coral species: the gorgonians Eunicea flexuosa and Gorgonia ventalina, and the scleractinian Porites panamensis . The 20-bp PNA clamp was designed using DNA from E. flexuosa . Adding the PNA clamp during PCR increased the percentage of microbial reads in E. flexuosa samples more than 11-fold. Microbial community diversity was similar without- and with-PNA clamps, as were the relative frequencies of the ten most abundant ASVs (amplicon sequence variants), indicating that the clamps successfully blocked host DNA amplification while simultaneously increasing microbial DNA amplification proportionally across the most abundant taxa. The reduction of E. flexuosa DNA correlated with an increase in the abundance of rarer taxa. The clamp also increased the average percentage of microbial reads in another gorgonian, G. ventalina, by 8.6-fold without altering the microbial community beta diversity, and in a distantly related scleractinian coral, P. panamensis, by nearly double. The reduction of host contamination correlated with the number of nucleotide mismatches between the host amplicon and the PNA clamp. The PNA clamp costs as little as $0.48 per sample, making it an efficient and cost-effective solution to increase microbial sequence coverage for high-throughput sequencing of coral microbial communities.

We have recently demonstrated that collagenolytic Enterococcus faecalis plays a key and causative role in the pathogenesis of anastomotic leak, an uncommon but potentially lethal complication characterized by disruption of the intestinal wound following segmental removal of the colon (resection) and its reconnection (anastomosis). Here we hypothesized that comparative genetic analysis of E. faecalis isolates present at the anastomotic wound site before and after surgery would shed insight into the mechanisms by which collagenolytic strains are selected for and predominate at sites of anastomotic disruption. Whole genome optical mapping of four pairs of isolates from rat colonic tissue obtained following surgical resection (herein named “pre-op” isolates) and then 6 days later from the anastomotic site (herein named “post-op” isolates) demonstrated that the isolates with higher collagenolytic activity formed a distinct cluster. In order to perform analysis at a deeper level, a single pair of E. faecalis isolates (16A pre-op and 16A post-op) was selected for whole genome sequencing and assembled using a hybrid assembly algorithm. Comparative genomics demonstrated absence of multiple gene clusters, notably a pathogenicity island in the post-op isolate. No differences were found in the fsr-gelE-sprE genes (EF1817-1822) responsible for regulation and production of collagenolytic activity. Analysis of unique genes among the 16A pre-op and post-op isolates revealed the predominance of transporter systems-related genes in the pre-op isolate and phage-related and hydrolytic enzyme-encoding genes in the post-op isolate. Despite genetic differences observed between pre-op and post-op isolates, the precise genetic determinants responsible for their differential expression of collagenolytic activity remains unknown.

While most bacterial and archaeal taxa living in surface soils remain undescribed, this problem is exacerbated in deeper soils, owing to the unique oligotrophic conditions found in the subsurface. Additionally, previous studies of soil microbiomes have focused almost exclusively on surface soils, even though the microbes living in deeper soils also play critical roles in a wide range of biogeochemical processes. We examined soils collected from 20 distinct profiles across the United States to characterize the bacterial and archaeal communities that live in subsurface soils and to determine whether there are consistent changes in soil microbial communities with depth across a wide range of soil and environmental conditions. We found that bacterial and archaeal diversity generally decreased with depth, as did the degree of similarity of microbial communities to those found in surface horizons. We observed five phyla that consistently increased in relative abundance with depth across our soil profiles: Chloroflexi, Nitrospirae, Euryarchaeota, and candidate phyla GAL15 and Dormibacteraeota (formerly AD3). Leveraging the unusually high abundance of Dormibacteraeota at depth, we assembled genomes representative of this candidate phylum and identified traits that are likely to be beneficial in low-nutrient environments, including the synthesis and storage of carbohydrates, the potential to use carbon monoxide (CO) as a supplemental energy source, and the ability to form spores. Together these attributes likely allow members of the candidate phylum Dormibacteraeota to flourish in deeper soils and provide insight into the survival and growth strategies employed by the microbes that thrive in oligotrophic soil environments.IMPORTANCE Soil profiles are rarely homogeneous. Resource availability and microbial abundances typically decrease with soil depth, but microbes found in deeper horizons are still important components of terrestrial ecosystems. By studying 20 soil profiles across the United States, we documented consistent changes in soil bacterial and archaeal communities with depth. Deeper soils harbored communities distinct from those of the more commonly studied surface horizons. Most notably, we found that the candidate phylum Dormibacteraeota (formerly AD3) was often dominant in subsurface soils, and we used genomes from uncultivated members of this group to identify why these taxa are able to thrive in such resource-limited environments. Simply digging deeper into soil can reveal a surprising number of novel microbes with unique adaptations to oligotrophic subsurface conditions.

The Deblur sOTU counts table for the fecal samples used in the American Gut Project manuscript. The samples were trimmed to a common read length of 125nt, and processed by Deblur (Amir et al mSystems 2017). Blooms were removed (Amir et al mSystems 2017) and any sample with fewer than 1250 sequences was omitted. This table is not rarefied,.

The full American Gut Project mapping file, includes non-fecal samples.

The ITS protocol detailed here is designed to amplify fungal microbial eukaryotic lineages using paired-end community sequencing on the Illumina platform with primersITS1f-ITS2 (EMP.ITSkabir).

Intestinal mucus layer disruption and gut microflora modification in conjunction with tight junction (TJ) changes can increase colonic permeability that allows bacterial dissemination and intestinal and systemic disease. We showed previously that Citrobacter rodentium (CR)-induced colonic crypt hyperplasia and/or colitis is regulated by a functional cross-talk between the Notch and Wnt/β-catenin pathways. In the current study, mucus analysis in the colons of CR-infected (108 CFUs) and Notch blocker Dibenzazepine (DBZ, i.p.; 10μmol/Kg b.w.)-treated mice revealed significant alterations in the composition of trace O-glycans and complex type and hybrid N-glycans, compared to CR-infected mice alone that preceded/accompanied alterations in 16S rDNA microbial community structure and elevated EUB338 staining. While mucin-degrading bacterium, Akkermansia muciniphila (A. muciniphila) along with Enterobacteriaceae belonging to Proteobacteria phyla increased in the feces, antimicrobial peptides Angiogenin-4, Intelectin-1 and Intelectin-2, and ISC marker Dclk1, exhibited dramatic decreases in the colons of CR-infected/DBZ-treated mice. Also evident was a loss of TJ and adherens junction protein immuno-staining within the colonic crypts that negatively impacted paracellular barrier. These changes coincided with the loss of Notch signaling and exacerbation of mucosal injury. In response to a cocktail of antibiotics (Metronidazole/ciprofloxacin) for 10 days, there was increased survival that coincided with: i) decreased levels of Proteobacteria, ii) elevated Dclk1 levels in the crypt and, iii) reduced paracellular permeability. Thus, enteric infections that interfere with Notch activity may promote mucosal dysbiosis that is preceded by changes in mucus composition. Controlled use of antibiotics seems to alleviate gut dysbiosis but may be insufficient to promote colonic crypt regeneration.

The 18S protocol detailed here is designed to amplify eukaryotes broadly with a focus on microbial eukaryotic lineages. The primers target the 18S SSU rRNA and are based on those of Amaral-Zettler et al. (2009). The constructs are designed to be used with the Illumina platform. For running these libraries on the MiSeq and HiSeq, please make sure you read the supplementary methods of Caporaso et al. (2012). You will need to make your sample more complex by adding 5-10% PhiX to your run. The outlines of the protocol are the same as the 16S protocol, but different primers, PCR conditions, and sequencing primers are used. In addition, we have designed a blocking primer that reduces the amplification of vertebrate host DNA to be used on host-associated samples, especially those that have a low eukaryotic biomass. Blocking primer strategy is based on Vestheim et al. (2008).