isolateR: an R package for generating microbial libraries from Sanger sequencing data.

MOTIVATION: Sanger sequencing of taxonomic marker genes (e.g., 16S/18S/ITS/rpoB/cpn60) represents the leading method for identifying a wide range of microorganisms including bacteria, archaea, and fungi. However, the manual processing of sequence data and limitations associated with conventional BLAST searches impede the efficient generation of strain libraries essential for cataloging microbial diversity and discovering novel species. RESULTS: isolateR addresses these challenges by implementing a standardized and scalable three-step pipeline that includes: 1) automated batch processing of Sanger sequence files, 2) taxonomic classification via global alignment to type strain databases in accordance with the latest international nomenclature standards, and 3) straightforward creation of strain libraries and handling of clonal isolates, with the ability to set customizable sequence dereplication thresholds and combine data from multiple sequencing runs into a single library. The tool's user-friendly design also features interactive HTML outputs that simplify data exploration and analysis. Additionally, in silico benchmarking done on two comprehensive human gut genome catalogues (IMGG and Hadza hunter-gather populations) showcase the proficiency of isolateR in uncovering and cataloging the nuanced spectrum of microbial diversity, advocating for a more targeted and granular exploration within individual hosts to achieve the highest strain-level resolution possible when generating culture collections. AVAILABILITY: isolateR is available at: https://github.com/bdaisley/isolateR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metagenomics: a path to understanding the gut microbiome.

The gut microbiome is a major determinant of host health, yet it is only in the last 2 decades that the advent of next-generation sequencing has enabled it to be studied at a genomic level. Shotgun sequencing is beginning to provide insight into the prokaryotic as well as eukaryotic and viral components of the gut community, revealing not just their taxonomy, but also the functions encoded by their collective metagenome. This revolution in understanding is being driven by continued development of sequencing technologies and in consequence necessitates reciprocal development of computational approaches that can adapt to the evolving nature of sequence datasets. In this review, we provide an overview of current bioinformatic strategies for handling metagenomic sequence data and discuss their strengths and limitations. We then go on to discuss key technological developments that have the potential to once again revolutionise the way we are able to view and hence understand the microbiome.

Optimization of metabolomics of defined in vitro gut microbial ecosystems.

The metabolic functionality of a microbial community is a key to the understanding of its inherent ecological processes and the interaction with the host. However, the study of the human gut microbiota is hindered by the complexity of this ecosystem. One way to resolve this issue is to derive defined communities that may be cultured ex vivo in bioreactor systems and used to approximate the native ecosystem. Doing so has the advantage of experimental reproducibility and ease of sampling, and furthermore, in-depth analysis of metabolic processes becomes highly accessible. Here, we review the use of bioreactor systems for ex vivo modelling of the human gut microbiota with respect to analysis of the metabolic output of the microbial ecosystem, and discuss the possibility of mechanistic insights using these combined techniques. We summarize the different platforms currently used for metabolomics and suitable for analysis of gut microbiota samples from a bioreactor system. With the help of representative datasets obtained from a series of bioreactor runs, we compare the outputs of both NMR and mass spectrometry based approaches in terms of their coverage, sensitivity and quantification. We also discuss the use of untargeted and targeted analyses in mass spectroscopy and how these techniques can be combined for optimal biological interpretation. Potential solutions for linking metabolomic and phylogenetic datasets with regards to active, key species within the ecosystem will be presented.

Metabolomic analysis of human fecal microbiota: a comparison of feces-derived communities and defined mixed communities.

The extensive impact of the human gut microbiota on its human host calls for a need to understand the types of communication that occur among the bacteria and their host. A metabolomics approach can provide a snapshot of the microbe-microbe interactions occurring as well as variations in the microbes from different hosts. In this study, metabolite profiles from an anaerobic continuous stirred-tank reactors (CSTR) system supporting the growth of several consortia of bacteria representative of the human gut were established and compared. Cell-free supernatant samples were analyzed by 1D (1)H nuclear magnetic resonance (NMR) spectroscopy, producing spectra representative of the metabolic activity of a particular community at a given time. Using targeted profiling, specific metabolites were identified and quantified on the basis of NMR analyses. Metabolite profiles discriminated each bacterial community examined, demonstrating that there are significant differences in the microbiota metabolome between each cultured community. We also found unique compounds that were identifying features of individual bacterial consortia. These findings are important because they demonstrate that metabolite profiles of gut microbial ecosystems can be constructed by targeted profiling of NMR spectra. Moreover, examination of these profiles sheds light on the type of microbes present in the gut and their metabolic interactions.

A pro-inflammatory gut mucosal cytokine response is associated with mild COVID-19 disease and superior induction of serum antibodies.

The relationship between gastrointestinal tract infection, the host immune response, and the clinical outcome of disease is not well understood in COVID-19. We sought to understand the effect of intestinal immune responses to SARS-CoV-2 on patient outcomes including the magnitude of systemic antibody induction. Combining two prospective cohort studies, International Severe Acute Respiratory and emerging Infections Consortium Comprehensive Clinical Characterisations Collaboration (ISARIC4C) and Integrated Network for Surveillance, Trials and Investigations into COVID-19 Transmission (INSTINCT), we acquired samples from 88 COVID-19 cases representing the full spectrum of disease severity and analysed viral RNA and host gut cytokine responses in the context of clinical and virological outcome measures. There was no correlation between the upper respiratory tract and faecal viral loads. Using hierarchical clustering, we identified a group of fecal cytokines including Interleukin-17A, Granulocyte macrophage colony-stimulating factor, Tumor necrosis factorα, Interleukin-23, and S100A8, that were transiently elevated in mild cases and also correlated with the magnitude of systemic anti-Spike-receptor-binding domain antibody induction. Receiver operating characteristic curve analysis showed that expression of these gut cytokines at study enrolment in hospitalised COVID-19 cases was associated negatively with overall clinical severity implicating a protective role in COVID-19. This suggests that a productive intestinal immune response may be beneficial in the response to a respiratory pathogen and a biomarker of a successful barrier response.

The effects of a hydrolyzed protein diet on the plasma, fecal and urine metabolome in cats with chronic enteropathy.

Hydrolyzed protein diets are extensively used to treat chronic enteropathy (CE) in cats. However, the biochemical effects of such a diet on feline CE have not been characterized. In this study an untargeted 1H nuclear magnetic resonance spectroscopy-based metabolomic approach was used to compare the urinary, plasma, and fecal metabolic phenotypes of cats with CE to control cats with no gastrointestinal signs recruited at the Royal Veterinary College (RVC). In addition, the biomolecular consequences of a hydrolyzed protein diet in cats with CE was also separately determined in cats recruited from the RVC (n = 16) and the University of Bristol (n = 24) and whether these responses differed between dietary responders and non-responders. Here, plasma metabolites related to energy and amino acid metabolism significantly varied between CE and control cats in the RVC cohort. The hydrolyzed protein diet modulated the urinary metabolome of cats with CE (p = 0.005) in both the RVC and Bristol cohort. In the RVC cohort, the urinary excretion of phenylacetylglutamine, p-cresyl-sulfate, creatinine and taurine at diagnosis was predictive of dietary response (p = 0.025) although this was not observed in the Bristol cohort. Conversely, in the Bristol cohort plasma betaine, glycerol, glutamine and alanine at diagnosis was predictive of outcome (p = 0.001), but these same results were not observed in the RVC cohort. The biochemical signature of feline CE in the RVC cohort was consistent with that identified in human and animal models of inflammatory bowel disease. The hydrolyzed protein diet had the same effect on the urinary metabolome of cats with CE at both sites. However, biomarkers that were predictive of dietary response at diagnosis differed between the 2 sites. This may be due to differences in disease severity, disease heterogeneity, factors unrelated to the disease or small sample size at both sites. As such, further studies utilizing larger number of cats are needed to corroborate these findings.

The effect of a hydrolyzed protein diet on the fecal microbiota in cats with chronic enteropathy.

The effect of a hydrolyzed protein diet on the fecal microbiota has not been studied in feline chronic enteropathy (CE). Our study aimed to (1) compare the fecal microbiota of cats with CE to control cats with no gastrointestinal signs and (2) determine the effect of a hydrolyzed protein diet on the fecal microbiota of cats with CE and whether this differs between dietary responders and non-responders. The fecal microbiome of cats with CE (n = 36) showed decreased α-diversity in terms of genus richness (P = 0.04) and increased ß-diversity in terms of Bray-Curtis Dissimilarity (P < 0.001) compared to control cats (n = 14). Clostridium was the only genera significantly over-represented in cats with CE compared to control cats (adjusted P < 0.1). After 6-weeks of feeding the diet, fifteen cats were classified as responders and 18 as non-responders, based on clinical signs. At the genus level, α-diversity was increased in non-responders versus responders at diagnosis, but decreased after dietary intervention in both groups (P < 0.05). At the family level, non-responders became increasingly dissimilar after dietary intervention (P = 0.012). In general, the abundance of bacteria decreased with feeding a hydrolyzed diet, with the genera most significantly affected being more frequently observed in non-responders. Bifidobacterium was the only genus that increased significantly in abundance post-diet and this effect was observed in both responders and non-responders. Both Oscillibacter and Desulfovibrionaceae_unclassified were most abundant in non-responders at diagnosis but were rarely observed post diet in neither responders nor non-responders. Cats with CE had similar microbiota changes to those described in human inflammatory bowel disease. Whether the presence of Oscillibacter and Desulfovibrionaceae_unclassified are indicators of non-response to the diet at diagnosis requires further investigation. Despite the hydrolyzed diet reducing α-diversity in all cats with CE, this did not resolve gastrointestinal signs in some cats. However, responders metabolized the diet in a similar manner, reflected by sustained ß-diversity, while the microbiome of non-responders became increasingly dissimilar compared to diagnosis at the family level. Therefore, the microbiome may not be as tightly regulated in cats with CE that are non-responders and therefore, these cats would require additional therapy for remission of clinical signs.

1D 1 H NMR as a Tool for Fecal Metabolomics.

Metabolomic studies allow a deeper understanding of the processes of a given ecological community than nucleic acid-based surveys alone. In the case of the gut microbiota, a metabolic profile of, for example, a fecal sample provides details about the function and interactions within the distal region of the gastrointestinal tract, and such a profile can be generated in a number of different ways. This unit elaborates on the use of 1D 1 H NMR spectroscopy as a commonly used method to characterize small-molecule metabolites of the fecal metabonome (meta-metabolome). We describe a set of protocols for the preparation of fecal water extraction, storage, scanning, measurement of pH, and spectral processing and analysis. We also compare the effects of various sample storage conditions for processed and unprocessed samples to provide a framework for comprehensive analysis of small molecules from stool-derived samples. © 2020 Wiley Periodicals LLC Basic Protocol 1: Extracting fecal water from crude fecal samples Alternate Protocol 1: Extracting fecal water from small crude fecal samples Basic Protocol 2: Acquiring NMR spectra of metabolite samples Alternate Protocol 2: Acquiring NMR spectra of metabolite samples using Bruker spectrometer running TopSpin 3.x Alternate Protocol 3: Acquiring NMR spectra of metabolite samples by semiautomated process Basic Protocol 3: Measuring sample pH Support Protocol 1: Cleaning NMR tubes Basic Protocol 4: Processing raw spectra data Basic Protocol 5: Profiling spectra Support Protocol 2: Spectral profiling of sugars and other complex metabolites.

Effects of Antibiotic Pretreatment of an Ulcerative Colitis-Derived Fecal Microbial Community on the Integration of Therapeutic Bacteria In Vitro.

Fecal microbiota transplantation (FMT) is a proposedly useful strategy for the treatment of gastrointestinal (GI) disorders through remediation of the patient gut microbiota. However, its therapeutic success has been variable, necessitating research to uncover mechanisms that improve patient response. Antibiotic pretreatment has been proposed as one method to enhance the success rate by increasing niche availability for introduced species. Several limitations hinder exploring this hypothesis in clinical studies, such as deleterious side effects and the development of antimicrobial resistance in patients. Thus, the purpose of this study was to evaluate the use of an in vitro, bioreactor-based, colonic ecosystem model as a form of preclinical testing by determining how pretreatment with the antibiotic rifaximin influenced engraftment of bacterial strains sourced from a healthy donor into an ulcerative colitis-derived defined microbial community. Distinct species integrated under the pretreated and untreated conditions, with the relative rifaximin resistance of the microbial strains being an important influencer. However, both conditions resulted in the integration of taxa from Clostridium clusters IV and XIVa, a concomitant reduction of Proteobacteria, and similar decreases in metabolites associated with poor health status. Our results agree with the findings of similar research in the clinic by others, which observed no difference in primary patient outcomes whether or not patients were given rifaximin prior to FMT. We therefore conclude that our model is useful for screening for antibiotics that could improve efficacy of FMT when used as a pretreatment.IMPORTANCE Patients with gastrointestinal disorders often exhibit derangements in their gut microbiota, which can exacerbate their symptoms. Replenishing these ecosystems with beneficial bacteria through fecal microbiota transplantation is thus a proposedly useful therapeutic; however, clinical success has varied, necessitating research into strategies to improve outcomes. Antibiotic pretreatment has been suggested as one such approach, but concerns over harmful side effects have hindered testing this hypothesis clinically. Here, we evaluate the use of bioreactors supporting defined microbial communities derived from human fecal samples as models of the colonic microbiota in determining the effectiveness of antibiotic pretreatment. We found that relative antimicrobial resistance was a key determinant of successful microbial engraftment with rifaximin (broad-spectrum antibiotic) pretreatment, despite careful timing of the application of the therapeutic agents, resulting in distinct species profiles from those of the control but with similar overall outcomes. Our model had results comparable to the clinical findings and thus can be used to screen for useful antibiotics.

Effects of defined gut microbial ecosystem components on virulence determinants of Clostridioides difficile.

Many cases of Clostridioides difficile infection (CDI) are poorly responsive to standard antibiotic treatment strategies, and often patients suffer from recurrent infections characterized by severe diarrhea. Our group previously reported the successful cure of two patients with recurrent CDI using a standardized stool-derived microbial ecosystem therapeutic (MET-1). Using an in vitro model of the distal gut to support bacterial communities, we characterized the metabolite profiles of two defined microbial ecosystems derived from healthy donor stool (DEC58, and a subset community, MET-1), as well as an ecosystem representative of a dysbiotic state (ciprofloxacin-treated DEC58). The growth and virulence determinants of two C. difficile strains were then assessed in response to components derived from the ecosystems. CD186 (ribotype 027) and CD973 (ribotype 078) growth was decreased upon treatment with DEC58 metabolites compared to ciprofloxacin-treated DEC58 metabolites. Furthermore, CD186 TcdA and TcdB secretion was increased following treatment with ciprofloxacin-treated DEC58 spent medium compared to DEC58 spent medium alone. The net metabolic output of C. difficile was also modulated in response to spent media from defined microbial ecosystems, although several metabolite levels were divergent across the two strains examined. Further investigation of these antagonistic properties will guide the development of microbiota-based therapeutics for CDI.

Treating cell culture media with UV irradiation against adventitious agents: minimal impact on CHO performance.

Sterility of cell culture media is an important concern in biotherapeutic processing. In large scale biotherapeutic production, a unit contamination of cell culture media can have costly effects. Ultraviolet (UV) irradiation is a sterilization method effective against bacteria and viruses while being non-thermal and non-adulterating in its mechanism of action. This makes UV irradiation attractive for use in sterilization of cell culture media. The objective of this study was to evaluate the effect of UV irradiation of cell culture media in terms of chemical composition and the ability to grow cell cultures in the treated media. The results showed that UV irradiation of commercial cell culture media at relevant disinfection doses impacted the chemical composition of the media with respect to several carboxylic acids, and to a minimal extent, amino acids. The cumulative effect of these changes, however, did not negatively influence the ability to culture Chinese Hamster Ovary cells, as evaluated by cell viability, growth rate, and protein titer measurements in simple batch growth compared with the same cells cultured in control media exposed to visible light.