Genomics and synthetic community experiments uncover the key metabolic roles of acetic acid bacteria in sourdough starter microbiomes.

While research on the sourdough microbiome has primarily focused on lactic acid bacteria (LAB) and yeast, recent studies have found that acetic acid bacteria (AAB) are also common members. However, the ecology, genomic diversity, and functional contributions of AAB in sourdough remain unknown. To address this gap, we sequenced 29 AAB genomes, including three that represent putatively novel species, from a collection of over 500 sourdough starters surveyed globally from community scientists. We found variations in metabolic traits related to carbohydrate utilization, nitrogen metabolism, and alcohol production, as well as in genes related to mobile elements and defense mechanisms. Sourdough AAB genomes did not cluster when compared to AAB isolated from other environments, although a subset of gene functions was enriched in sourdough isolates. The lack of a sourdough-specific genomic cluster may reflect the nomadic lifestyle of AAB. To assess the consequences of AAB on the emergent function of sourdough starter microbiomes, we constructed synthetic starter microbiomes, varying only the AAB strain included. All AAB strains increased the acidification of synthetic sourdough starters relative to yeast and LAB by 18.5% on average. Different strains of AAB had distinct effects on the profile of synthetic starter volatiles. Taken together, our results begin to define the ways in which AAB shape emergent properties of sourdough and suggest that differences in gene content resulting from intraspecies diversification can have community-wide consequences on emergent function. IMPORTANCE: This study is a comprehensive genomic and ecological survey of acetic acid bacteria (AAB) isolated from sourdough starters. By combining comparative genomics with manipulative experiments using synthetic microbiomes, we demonstrate that even strains with >97% average nucleotide identity can shift important microbiome functions, underscoring the importance of species and strain diversity in microbial systems. We also demonstrate the utility of sourdough starters as a model system to understand the consequences of genomic diversity at the strain and species level on multispecies communities. These results are also relevant to industrial and home-bakers as we uncover the importance of AAB in shaping properties of sourdough starters that have direct impacts on sensory notes and the quality of sourdough bread.

High-throughput quantification of microbial-derived organic acids in mucin-rich samples via reverse phase high performance liquid chromatography.

Organic acids (short chain fatty acids, amino acids, etc.) are common metabolic byproducts of commensal bacteria of the gut and oral cavity in addition to microbiota associated with chronic infections of the airways, skin, and soft tissues. A ubiquitous characteristic of these body sites in which mucus-rich secretions often accumulate in excess, is the presence of mucins; high molecular weight (HMW), glycosylated proteins that decorate the surfaces of non-keratinized epithelia. Owing to their size, mucins complicate quantification of microbial-derived metabolites as these large glycoproteins preclude use of 1D and 2D gel approaches and can obstruct analytical chromatography columns. Standard approaches for quantification of organic acids in mucin-rich samples typically rely on laborious extractions or outsourcing to laboratories specializing in targeted metabolomics. Here we report a high-throughput sample preparation process that reduces mucin abundance and an accompanying isocratic reverse phase high performance liquid chromatography (HPLC) method that enables quantification of microbial-derived organic acids. This approach allows for accurate quantification of compounds of interest (0.01 mM - 100 mM) with minimal sample preparation, a moderate HPLC method run time, and preservation of both guard and analytical column integrity. This approach paves the way for further analyses of microbial-derived metabolites in complex clinical samples.

Developing and deploying an integrated workshop curriculum teaching computational skills for reproducible research.

Inspired by well-established material and pedagogy provided by The Carpentries (Wilson, 2016), we developed a two-day workshop curriculum that teaches introductory R programming for managing, analyzing, plotting and reporting data using packages from the tidyverse (Wickham et al., 2019), the Unix shell, version control with git, and GitHub. While the official Software Carpentry curriculum is comprehensive, we found that it contains too much content for a two-day workshop. We also felt that the independent nature of the lessons left learners confused about how to integrate the newly acquired programming skills in their own work. Thus, we developed a new curriculum that aims to teach novices how to implement reproducible research principles in their own data analysis. The curriculum integrates live coding lessons with individual-level and group-based practice exercises, and also serves as a succinct resource that learners can reference both during and after the workshop. Moreover, it lowers the entry barrier for new instructors as they do not have to develop their own teaching materials or sift through extensive content. We developed this curriculum during a two-day sprint, successfully used it to host a two-day virtual workshop with almost 40 participants, and updated the material based on instructor and learner feedback. We hope that our new curriculum will prove useful to future instructors interested in teaching workshops with similar learning objectives.

Anaerobic Microbiota Derived from the Upper Airways Impact Staphylococcus aureus Physiology.

Staphylococcus aureus is associated with the development of persistent and severe inflammatory diseases of the upper airways. Yet, S. aureus is also carried asymptomatically in the sinonasal cavity of ∼50% of healthy adults. The causes of this duality and host and microbial factors that tip the balance between S. aureus pathogenesis and commensalism are poorly understood. We have shown that by degrading mucins, anaerobic microbiota support the growth of airway pathogens by liberating metabolites that are otherwise unavailable. Given the widely reported culture-based detection of anaerobes from individuals with chronic rhinosinusitis (CRS), here we tested our hypothesis that CRS microbiota is characterized by a mucin-degrading phenotype that alters S. aureus physiology. Using 16S rRNA gene sequencing, we indeed observed an increased prevalence and abundance of anaerobes in CRS relative to non-CRS controls. PICRUSt2-based functional predictions suggested increased mucin degradation potential among CRS microbiota that was confirmed by direct enrichment culture. Prevotella, Fusobacterium, and Streptococcus comprised a core mucin-degrading community across CRS subjects that generated a nutrient pool that augmented S. aureus growth on mucin as a carbon source. Finally, using transcriptome sequencing (RNA-seq), we observed that S. aureus transcription is profoundly altered in the presence of mucin-derived metabolites, though expression of several key metabolism- and virulence-associated pathways varied between CRS-derived bacterial communities. Together, these data support a model in which S. aureus metabolism and virulence in the upper airways are dependent upon the composition of cocolonizing microbiota and the metabolites they exchange.

Diversity of cystic fibrosis chronic rhinosinusitis microbiota correlates with different pathogen dominance.

Chronic rhinosinusitis (CRS) affects nearly all individuals with cystic fibrosis (CF) and is thought to serve as a reservoir for microbiota that subsequently colonize the lung. To better understand the microbial ecology of CRS, we generated a 16S rRNA gene sequencing profile of sinus mucus from CF-CRS patients. We show that CF-CRS sinuses harbor bacterial diversity not entirely captured by clinical culture. Culture data consistently identified the dominant organism in most patients, though lower abundance bacteria were not always identified. We also demonstrate that bacterial communities dominated by Staphylococcus spp. were significantly more diverse compared to those dominated by Pseudomonas spp. Diversity was not significantly associated with clinical factors or patient age, however, younger subjects yielded a much wider range of bacterial diversity. These data mirror bacterial community dynamics in the lung and provide additional insight into the role of sinus microbiota in chronic airway disease progression.

Bioorthogonal non-canonical amino acid tagging reveals translationally active subpopulations of the cystic fibrosis lung microbiota.

Culture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires comprehensive understanding of their ecophysiology at the site of infection. We hypothesize that only a subset of CF microbiota are translationally active and that these activities vary between subjects. Here, we apply bioorthogonal non-canonical amino acid tagging (BONCAT) to visualize and quantify bacterial translational activity in expectorated sputum. We report that the percentage of BONCAT-labeled (i.e. active) bacterial cells varies substantially between subjects (6-56%). We use fluorescence-activated cell sorting (FACS) and genomic sequencing to assign taxonomy to BONCAT-labeled cells. While many abundant taxa are indeed active, most bacterial species detected by conventional molecular profiling show a mixed population of both BONCAT-labeled and unlabeled cells, suggesting heterogeneous growth rates in sputum. Differentiating translationally active subpopulations adds to our evolving understanding of CF lung disease and may help guide antibiotic therapies targeting bacteria most likely to be susceptible.

US Immigration Westernizes the Human Gut Microbiome.

Many US immigrant populations develop metabolic diseases post immigration, but the causes are not well understood. Although the microbiome plays a role in metabolic disease, there have been no studies measuring the effects of US immigration on the gut microbiome. We collected stool, dietary recalls, and anthropometrics from 514 Hmong and Karen individuals living in Thailand and the United States, including first- and second-generation immigrants and 19 Karen individuals sampled before and after immigration, as well as from 36 US-born European American individuals. Using 16S and deep shotgun metagenomic DNA sequencing, we found that migration from a non-Western country to the United States is associated with immediate loss of gut microbiome diversity and function in which US-associated strains and functions displace native strains and functions. These effects increase with duration of US residence and are compounded by obesity and across generations.

16S rRNA gene sequencing reveals site-specific signatures of the upper and lower airways of cystic fibrosis patients.

BACKGROUND: Metastasis of upper airway microbiota may have significant implications in the development of chronic lung disease. Here, we compare bacterial communities of matched sinus and lung mucus samples from cystic fibrosis (CF) subjects undergoing endoscopic surgery for treatment of chronic sinusitis. METHODS: Mucus from one maxillary sinus and expectorated sputum were collected from twelve patients. 16S rRNA gene sequencing was then performed on sample pairs to compare the structure and function of CF airway microbiota. RESULTS: Bacterial diversity was comparable between airway sites, though sinuses harbored a higher prevalence of dominant microorganisms. Ordination analyses revealed that samples clustered more consistently by airway niche rather than by individual. Finally, predicted metagenomes suggested that anaerobiosis was enriched in the lung. CONCLUSIONS: Our findings indicate that while the lung may be seeded by individual sinus pathogens, airway microenvironments harbor distinct bacterial communities that should be considered in selecting antimicrobial therapies.

Integrated next-generation sequencing of 16S rDNA and metaproteomics differentiate the healthy urine microbiome from asymptomatic bacteriuria in neuropathic bladder associated with spinal cord injury.

BACKGROUND: Clinical dogma is that healthy urine is sterile and the presence of bacteria with an inflammatory response is indicative of urinary tract infection (UTI). Asymptomatic bacteriuria (ABU) represents the state in which bacteria are present but the inflammatory response is negligible. Differentiating ABU from UTI is diagnostically challenging, but critical because overtreatment of ABU can perpetuate antimicrobial resistance while undertreatment of UTI can result in increased morbidity and mortality. In this study, we describe key characteristics of the healthy and ABU urine microbiomes utilizing 16S rRNA gene (16S rDNA) sequencing and metaproteomics, with the future goal of utilizing this information to personalize the treatment of UTI based on key individual characteristics. METHODS: A cross-sectional study of 26 healthy controls and 27 healthy subjects at risk for ABU due to spinal cord injury-related neuropathic bladder (NB) was conducted. Of the 27 subjects with NB, 8 voided normally, 8 utilized intermittent catheterization, and 11 utilized indwelling Foley urethral catheterization for bladder drainage. Urine was obtained by clean catch in voiders, or directly from the catheter in subjects utilizing catheters. Urinalysis, urine culture and 16S rDNA sequencing were performed on all samples, with metaproteomic analysis performed on a subsample. RESULTS: A total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline. Urine microbiomes differ by normal bladder function vs. NB, gender, type of bladder catheter utilized, and duration of NB. The top ten bacterial taxa showing the most relative abundance and change among samples were Lactobacillales, Enterobacteriales, Actinomycetales, Bacillales, Clostridiales, Bacteroidales, Burkholderiales, Pseudomonadales, Bifidobacteriales and Coriobacteriales. Metaproteomics confirmed the 16S rDNA results, and functional human protein-pathogen interactions were noted in subjects where host defenses were initiated. CONCLUSIONS: Counter to clinical belief, healthy urine is not sterile. The healthy urine microbiome is characterized by a preponderance of Lactobacillales in women and Corynebacterium in men. The presence and duration of NB and method of urinary catheterization alter the healthy urine microbiome. An integrated approach of 16S rDNA sequencing with metaproteomics improves our understanding of healthy urine and facilitates a more personalized approach to prevention and treatment of infection.