WGS of intrauterine E. coli from cows with early postpartum uterine infection reveals a non-uterine specific genotype and virulence factors

Escherichia coli has been attributed to playing a major role in a cascade of events that affect the prevalence and severity of uterine disease in cattle. The objectives of this project were to (i) define the association between the prevalence of specific antimicrobial resistance and virulence factor genes in E. coli with the clinical status related to uterine infection, (ii) identify the genetic relationship between E. coli isolates from cows with diarrhea, with mastitis, and with and without metritis, and (iii) determine the association between the phenotypic and genotypic antimicrobial resistance identified on the E. coli isolated from postpartum cattle. Bacterial isolates (n = 148) were obtained from a larger cross-sectional study. Cows were categorized into one of three clinical groups before enrollment: metritis, cows with purulent discharge, and control cows. For genomic comparison, public genomes (n = 130) from cows with diarrhea, mastitis, and metritis were included in a genome-wide association study, to evaluate differences between the drug classes or the virulence factor category among clinical groups. A distinct E. coli genotype associated with metritis could not be identified. Instead, a high genetic diversity among the isolates from uterine sources was present. A virulence factor previously associated with metritis (fimH) using PCR was not associated with metritis. There was moderate accuracy for whole-genome sequencing to predict phenotypic resistance, which varied depending on the antimicrobial tested. Findings from this study contradict the traditional pathotype classification and the unique intrauterine E. coli genotype associated with metritis in dairy cows.IMPORTANCEMetritis is a common infectious disease in dairy cattle and the second most common reason for treating a cow with antimicrobials. The pathophysiology of the disease is complex and is not completely understood. Specific endometrial pathogenic Escherichia coli have been reported to be adapted to the endometrium and sometimes lead to uterine disease. Unfortunately, the specific genomic details of the endometrial-adapted isolates have not been investigated using enough genomes to represent the genomic diversity of this organism to identify specific virulence genes that are consistently associated with disease development and severity. Results from this study provide key microbial ecological advances by elucidating and challenging accepted concepts for the role of Intrauterine E. coli in metritis in dairy cattle, especially contradicting the existence of a unique intrauterine E. coli genotype associated with metritis in dairy cows, which was not found in our study.

Safety profile and effects on the peripheral immune response of fecal microbiota transplantation in clinically healthy dogs

BACKGROUND

Fecal microbiota transplantation (FMT) is increasingly used for gastrointestinal and extra-gastrointestinal diseases in veterinary medicine. However, its effects on immune responses and possible adverse events have not been systematically investigated.

HYPOTHESIS/OBJECTIVES

Determine the short-term safety profile and changes in the peripheral immune system after a single FMT administration in healthy dogs.

ANIMALS

Ten client-owned, clinically healthy dogs as FMT recipients, and 2 client-owned clinically healthy dogs as FMT donors.

METHODS

Prospective non-randomized clinical trial. A single rectal enema of 5 g/kg was given to clinically healthy canine recipients. During the 28 days after FMT administration, owners self-reported adverse events and fecal scores. On Days 0 (baseline), 1, 4, 10, and 28 after FMT, fecal and blood samples were collected. The canine fecal dysbiosis index (DI) was calculated using qPCR.

RESULTS

No significant changes were found in the following variables: CBC, serum biochemistry, C-reactive protein, serum cytokines (interleukins [IL]-2, -6, -8, tumor necrosis factor [TNF]-α), peripheral leukocytes (B cells, T cells, cluster of differentiation [CD]4+ T cells, CD8+ T cells, T regulatory cells), and the canine DI. Mild vomiting (n = 3), diarrhea (n = 4), decreased activity (n = 2), and inappetence (n = 1) were reported, and resolved without intervention.

CONCLUSIONS AND CLINICAL IMPORTANCE

Fecal microbiota transplantation did not significantly alter the evaluated variables and recipients experienced minimal adverse events associated with FMT administration. Fecal microbiota transplantation was not associated with serious adverse events, changes in peripheral immunologic variables, or the canine DI in the short-term.

Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

Impact of zinc supplementation on phenotypic antimicrobial resistance of fecal commensal bacteria from pre-weaned dairy calves

The objective of this study was to evaluate the impact of dietary zinc supplementation in pre-weaned dairy calves on the phenotypic antimicrobial resistance (AMR) of fecal commensal bacteria. A repository of fecal specimens from a random sample of calves block-randomized into placebo (n = 39) and zinc sulfate (n = 28) groups collected over a zinc supplementation clinical trial at the onset of calf diarrhea, calf diarrheal cure, and the last day of 14 cumulative days of zinc or placebo treatment were analyzed. Antimicrobial susceptibility testing was conducted for Enterococcus spp. (n = 167) and E. coli (n = 44), with one representative isolate of each commensal bacteria tested per sample. Parametric survival interval regression models were constructed to evaluate the association between zinc treatment and phenotypic AMR, with exponentiated accelerated failure time (AFT) coefficients adapted for MIC instead of time representing the degree of change in AMR (MIC Ratio, MR). Findings from our study indicated that zinc supplementation did not significantly alter the MIC in Enterococcus spp. for 13 drugs: gentamicin, vancomycin, ciprofloxacin, erythromycin, penicillin, nitrofurantoin, linezolid, quinupristin/dalfopristin, tylosin tartrate, streptomycin, daptomycin, chloramphenicol, and tigecycline (MR = 0.96-2.94, p > 0.05). In E. coli, zinc supplementation was not associated with resistance to azithromycin (MR = 0.80, p > 0.05) and ceftriaxone (MR = 0.95, p > 0.05). However, a significant reduction in E. coli MIC values was observed for ciprofloxacin (MR = 0.17, 95% CI 0.03-0.97) and nalidixic acid (MR = 0.28, 95% CI 0.15-0.53) for zinc-treated compared to placebo-treated calves. Alongside predictions of MIC values generated from these 17 AFT models, findings from this study corroborate the influence of age and antimicrobial exposure on phenotypic AMR.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Unveiling the microbiome during post-partum uterine infection: a deep shotgun sequencing approach to characterize the dairy cow uterine microbiome

BACKGROUND

The goal of this study was to assess the microbial ecology and diversity present in the uterus of post-partum dairy cows with and without metritis from 24 commercial California dairy farms using shotgun metagenomics. A set subset of 95 intrauterine swab samples, taken from a larger selection of 307 individual cow samples previously collected, were examined for α and β diversity and differential abundance associated with metritis. Cows within 21 days post-partum were categorized into one of three clinical groups during sample collection: control (CT, n = 32), defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge; metritis (MET, n = 33), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; and purulent discharge cows (PUS, n = 31), defined as a non-fetid purulent or mucopurulent vaginal discharge.

RESULTS

All three clinical groups (CT, MET, and PUS) were highly diverse, with the top 12 most abundant genera accounting for 10.3%, 8.8%, and 10.1% of mean relative abundance, respectively. The α diversity indices revealed a lower diversity from samples collected from MET and PUS when compared to CT cows. PERMANOVA statistical testing revealed a significant difference (P adjusted < 0.01) in the diversity of genera between CT and MET samples (R2 = 0.112, P = 0.003) and a non-significant difference between MET and PUS samples (R2 = 0.036, P = 0.046). ANCOM-BC analysis revealed that from the top 12 most abundant genera, seven genera were increased in the natural log fold change (LFC) of abundance in MET when compared to CT samples: Bacteroides, Clostridium, Fusobacterium, Phocaeicola, Porphyromonas, Prevotella, and Streptococcus. Two genera, Dietzia and Microbacterium, were decreased in natural LFC of abundance when comparing MET (regardless of treatment) and CT, while no changes in natural LFC of abundance were observed for Escherichia, Histophilus, and Trueperella.

CONCLUSIONS

The results presented here, are the current deepest shotgun metagenomic analyses conducted on the bovine uterine microbiome to date (mean of 256,425 genus-level reads per sample). Our findings support that uterine samples from cows without metritis (CT) had increased α-diversity but decreased β-diversity when compared to metritis or PUS cows, characteristic of dysbiosis. In summary, our findings highlight that MET cows have an increased abundance of Bacteroides, Porphyromonas, and Fusobacterium when compared to CT and PUS, and support the need for further studies to better understand their potential causal role in metritis pathogenesis.

Microbial-Derived Tryptophan Metabolites and Their Role in Neurological Disease: Anthranilic Acid and Anthranilic Acid Derivatives

The gut microbiome provides the host access to otherwise indigestible nutrients, which are often further metabolized by the microbiome into bioactive components. The gut microbiome can also shift the balance of host-produced compounds, which may alter host health. One precursor to bioactive metabolites is the essential aromatic amino acid tryptophan. Tryptophan is mostly shunted into the kynurenine pathway but is also the primary metabolite for serotonin production and the bacterial indole pathway. Balance between tryptophan-derived bioactive metabolites is crucial for neurological homeostasis and metabolic imbalance can trigger or exacerbate neurological diseases. Alzheimer's, depression, and schizophrenia have been linked to diverging levels of tryptophan-derived anthranilic, kynurenic, and quinolinic acid. Anthranilic acid from collective microbiome metabolism plays a complex but important role in systemic host health. Although anthranilic acid and its metabolic products are of great importance for host-microbe interaction in neurological health, literature examining the mechanistic relationships between microbial production, host regulation, and neurological diseases is scarce and at times conflicting. This narrative review provides an overview of the current understanding of anthranilic acid's role in neurological health and disease, with particular focus on the contribution of the gut microbiome, the gut-brain axis, and the involvement of the three major tryptophan pathways.

Alpha-Gal Bound Aptamer and Vancomycin Synergistically Reduce Staphylococcus aureus Infection In Vivo

Methicillin-resistant Staphylococcus aureus (MRSA) is a pervasive and persistent threat that requires the development of novel therapies or adjuvants for existing ones. Aptamers, small single-stranded oligonucleotides that form 3D structures and can bind to target molecules, provide one possible therapeutic route, especially when presented in combination with current antibiotic applications. BALB/c α-1, 3-galactosyltransferase (-/-) knockout (GTKO) mice were infected with MRSA via tail vein IV and subsequently treated with the αSA31 aptamer (n = 4), vancomycin (n = 12), or αSA31 plus vancomycin (n = 12), with split doses in the morning and evening. The heart, lungs, liver, spleen, and kidneys were harvested upon necropsy for histological and qPCR analysis. All mice treated with αSA31 alone died, whereas 5/12 mice treated with vancomycin alone and 7/12 mice treated with vancomycin plus αSA31 survived the course of the experiment. The treatment of MRSA-infected mice with Vancomycin and an adjuvant aptamer αSA31 reduced disease persistence and dispersion as compared to treatment with either vancomycin SA31 alone, indicating the combination of antibiotic and specifically targeted αSA31 aptamer could be a novel way to control MRSA infection. The data further indicate that aptamers may serve as a potential therapeutic option for other emerging antibiotic resistant pathogens.

Different stages of the infection cycle are enriched for Campylobacter strains with distinct phenotypes and levels of fluoroquinolone resistance

Campylobacter species are the leading cause of bacterial diarrhoea worldwide and consumption of contaminated chicken meat is the most common route of infection. Chickens can be infected with multiple strains of Campylobacter and during the infection cycle this pathogen must survive a wide variety of environments. Numerous studies have reported a high degree of genetic variability in this pathogen that can use antigenic and phase variation to alter the expression of key phenotypes. In this study the phenotypic profile of isolates from freshly slaughtered chickens, chicken products in the supermarket and stool samples from infected patients were compared to identify phenotypic changes during the passage of the bacteria through the infection cycle. Isolates from different stages of the infection cycle had altered phenotypic profiles with isolates from human stool samples showing a lower ability to form a biofilm and an increased ability to associate with epithelial cells in vitro. Resistance to fluoroquinolones was found in all cohorts but at a much higher occurrence (94%) in isolates from supermarket chicken. Isolates displaying high levels of resistance to fluoroquinolones also were more likely to display a higher tolerance to growth in the presence of oxygen. In conclusion, isolates with specific phenotypes appear to be overly represented at different stages of the infection cycle suggesting that environmental stresses may be enriched for strains with these phenotypes.

Characterization of the equine placental microbial population in healthy pregnancies

In spite of controversy, recent studies present evidence that a microbiome is present in the human placenta. However, there is limited information about a potential equine placental microbiome. In the present study, we characterized the microbial population in the equine placenta (chorioallantois) of healthy prepartum (280 days of gestation, n = 6) and postpartum (immediately after foaling, 351 days of gestation, n = 11) mares, using 16S rDNA sequencing (rDNA-seq). In both groups, the majority of bacteria belonged to the phyla Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidota. The five most abundant genera were Bradyrhizobium, an unclassified Pseudonocardiaceae, Acinetobacter, Pantoea, and an unclassified Microbacteriaceae. Alpha diversity (p < 0.05) and beta diversity (p < 0.01) were significantly different between pre- and postpartum samples. Additionally, the abundance of 7 phyla and 55 genera was significantly different between pre- and postpartum samples. These differences suggest an effect of the caudal reproductive tract microbiome on the postpartum placental microbial DNA composition, since the passage of the placenta through the cervix and vagina during normal parturition had a significant influence on the composition of the bacteria found in the placenta when using 16S rDNA-seq. These data support the hypothesis that bacterial DNA is present in healthy equine placentas and opens the possibility for further exploration of the impact of the placental microbiome on fetal development and pregnancy outcome.

Characterization of rumen microbiome and metabolome from oro-esophageal tubing and rumen cannula in Holstein dairy cows

Less invasive rumen sampling methods, such as oro-esophageal tubing, became widely popular for exploring the rumen microbiome and metabolome. However, it remains unclear if such methods represent well the rumen contents from the rumen cannula technique. Herein, we characterized the microbiome and metabolome in the rumen content collected by an oro-esophageal tube and by rumen cannula in ten multiparous lactating Holstein cows. The 16S rRNA gene was amplified and sequenced using the Illumina MiSeq platform. Untargeted metabolome was characterized using gas chromatography of a time-of-flight mass spectrometer. Bacteroidetes, Firmicutes, and Proteobacteria were the top three most abundant phyla representing ~ 90% of all samples. Although the pH of oro-esophageal samples was greater than rumen cannula, we found no difference in alpha and beta-diversity among their microbiomes. The overall metabolome of oro-esophageal samples was slightly different from rumen cannula samples yet more closely related to the rumen cannula content as a whole, including its fluid and particulate fractions. Enrichment pathway analysis revealed a few differences between sampling methods, such as when evaluating unsaturated fatty acid pathways in the rumen. The results of the current study suggest that oro-esophageal sampling can be a proxy to screen the 16S rRNA rumen microbiome compared to the rumen cannula technique. The variation introduced by the 16S rRNA methodology may be mitigated by oro-esophageal sampling and the possibility of increasing experimental units for a more consistent representation of the overall microbial population. Studies should consider an under or over-representation of metabolites and specific metabolic pathways depending on the sampling method.

Salmonella enhances osteogenic differentiation in adipose-derived mesenchymal stem cells

The potential of mesenchymal stem cells (MSCs) for tissue repair and regeneration has garnered great attention. While MSCs are likely to interact with microbes at sites of tissue damage and inflammation, like in the gastrointestinal system, the consequences of pathogenic association on MSC activities have yet to be elucidated. This study investigated the effects of pathogenic interaction on MSC trilineage differentiation paths and mechanisms using model intracellular pathogen Salmonella enterica ssp enterica serotype Typhimurium. The examination of key markers of differentiation, apoptosis, and immunomodulation demonstrated that Salmonella altered osteogenic and chondrogenic differentiation pathways in human and goat adipose-derived MSCs. Anti-apoptotic and pro-proliferative responses were also significantly upregulated (p &lt; 0.05) in MSCs during Salmonella challenge. These results together indicate that Salmonella, and potentially other pathogenic bacteria, can induce pathways that influence both apoptotic response and functional differentiation trajectories in MSCs, highlighting that microbes have a potentially significant role as influencers of MSC physiology and immune activity.

Predicting Escherichia coli levels in manure using machine learning in weeping wall and mechanical liquid solid separation systems

An increased understanding of the interaction between manure management and public and environmental health has led to the development of Alternative Dairy Effluent Management Strategies (ADEMS). The efficiency of such ADEMS can be increased using mechanical solid-liquid-separator (SLS) or gravitational Weeping-Wall (WW) solid separation systems. In this research, using pilot study data from 96 samples, the chemical, physical, biological, seasonal, and structural parameters between SLS and WW of ADEM systems were compared. Parameters including sodium, potassium, total salts, volatile solids, pH, and E. coli levels were significantly different between the SLS and WW of ADEMS. The separated solid fraction of the dairy effluents had the lowest E. coli levels, which could have beneficial downstream implications in terms of microbial pollution control. To predict effluent quality and microbial pollution risk, we used Escherichia coli as the indicator organism, and a versatile machine learning, ensemble, stacked, super-learner model called E-C-MAN (Escherichia coli-Manure) was developed. Using pilot data, the E-C-MAN model was trained, and the trained model was validated with the test dataset. These results demonstrate that the heuristic E-C-MAN ensemble model can provide a pilot framework toward predicting Escherichia coli levels in manure treated by SLS or WW systems.

Two-component systems regulate bacterial virulence in response to the host gastrointestinal environment and metabolic cues

Two-component systems are ubiquitous signaling mechanisms in bacteria that enable intracellular changes from extracellular cues. These bacterial regulatory systems couple external stimuli to control genetic expression via an autophosphorylation cascade that transduces membrane signals to intracellular locations, thereby allowing bacteria to rapidly adapt to the changing environmental conditions. Well known to control basic cellular processes, it is evident that two-component systems also exercise control over virulence traits, such as motility, secretion systems, and stress responses that impact the complex cascade of networks that alter virulence traits. In the gastrointestinal system, cues for activation of virulence-related two-component systems include metal ions, host-derived metabolites, and gut conditions. The diversity and origin of these cues suggest that the host can exert control over enteric pathogenicity via regulation in the gastrointestinal system. With the rise in multi-drug resistant pathogens, the potential control of pathogenicity with host cues via two-component systems presents a potential alternative to antimicrobials. Though the signaling mechanism itself is well studied, to date there is no systematic review compiling the host-associated cues of two-component systems and virulence traits. This review highlights the direct link between the host gastrointestinal environment and pathogenicity by focusing on two-component systems that are associated with the genetic expression of virulence traits, and that are activated by host-derived cues. The direct link between the host gastrointestinal environment, metabolites, and pathogenicity established in this review both underscores the importance of host-derived cues on bacterial activity and presents an enticing therapeutic target in the fight against antimicrobial resistant pathogens.

Malnourishment affects gene expression along the length of the small intestine

Malnourishment is a risk factor for childhood mortality, jeopardizing the health of children by aggravating pneumonia/acute respiratory infections and diarrheal diseases. Malnourishment causes morphophysiological changes resulting in stunting and wasting that have long-lasting consequences such as cognitive deficit and metabolic dysfunction. Using a pig model of malnutrition, the interplay between the phenotypic data displayed by the malnourished animals, the gene expression pattern along the intestinal tract, microbiota composition of the intestinal contents, and hepatic metabolite concentrations from the same animals were correlated using a multi-omics approach. Samples from the duodenum, jejunum, and ileum of malnourished (protein and calorie-restricted diet) and full-fed (no dietary restrictions) piglets were subjected to RNA-seq. Gene co-expression analysis and phenotypic correlations were made with WGCNA, while the integration of transcriptome with microbiota composition and the hepatic metabolite profile was done using mixOmics. Malnourishment caused changes in tissue gene expression that influenced energetic balance, cell proliferation, nutrient absorption, and response to stress. Repression of antioxidant genes, including glutathione peroxidase, in coordination with induction of metal ion transporters corresponded to the hepatic metabolite changes. These data indicate oxidative stress in the intestine of malnourished animals. Furthermore, several of the phenotypes displayed by these animals could be explained by changes in gene expression.

Quantification of antibiotic resistance genes and mobile genetic in dairy manure

Background

Antibiotic resistance genes (ARGs) are considered to be emerging environmental contaminants of concern potentially posing risks to human and animal health, and this research studied the prevalence of antimicrobial resistance in dairy manure.

Methods

This study is focused on investigating prevalence of ARGs in California dairy farm manure under current common different manure management. A total of 33 manure samples were collected from multiple manure treatment conditions: (1) flushed manure (FM), (2) fresh pile (FP), (3) compost pile (CP), (4) primary lagoon (PL), and (5) secondary lagoon (SL). After DNA extraction, all fecal samples were screened by PCR for the presence of eight ARGs: four sulfonamide ARGs (sulI, sulII, sulIII, sulA), two tetracycline ARGs (tetW, tetO), two macrolide-lincosamide-streptogramin B (MLS_B) ARGs (ermB, ermF). Samples were also screened for two mobile genetic elements (MGEs) (intI1, tnpA), which are responsible for dissemination of ARGs. Quantitative PCR was then used to screen all samples for five ARGs (sulII, tetW, ermF, tnpA and intI1).

Results

Prevalence of genes varied among sample types, but all genes were detectable in different manure types. Results showed that liquid-solid separation, piling, and lagoon conditions had limited effects on reducing ARGs and MGEs, and the effect was only found significant on tetW (p = 0.01). Besides, network analysis indicated that sulII was associated with tnpA (p < 0.05), and Psychrobacter and Pseudomonas as opportunistic human pathogens, were potential ARG/MGE hosts (p < 0.05). This research indicated current different manure management practices in California dairy farms has limited effects on reducing ARGs and MGEs. Improvement of different manure management in dairy farms is thus important to mitigate dissemination of ARGs into the environment.

Whole Genome Sequencing of Pediatric Klebsiella pneumoniae Strains Reveals Important Insights Into Their Virulence-Associated Traits

Klebsiella pneumoniae is recognized as a common cause of nosocomial infections and outbreaks causing pneumonia, septicemia, and urinary tract infections. This opportunistic bacterium shows an increasing acquisition of antibiotic-resistance genes, which complicates treatment of infections. Hence, fast reliable strain typing methods are paramount for the study of this opportunistic pathogen’s multi-drug resistance genetic profiles. In this study, thirty-eight strains of K. pneumoniae isolated from the blood of pediatric patients were characterized by whole-genome sequencing and genomic clustering methods. Genes encoding β-lactamase were found in all the bacterial isolates, among which the bla_SHV variant was the most prevalent (53%). Moreover, genes encoding virulence factors such as fimbriae, capsule, outer membrane proteins, T4SS and siderophores were investigated. Additionally, a multi-locus sequence typing (MLST) analysis revealed 24 distinct sequence types identified within the isolates, among which the most frequently represented were ST76 (16%) and ST70 (11%). Based on LPS structure, serotypes O1 and O3 were the most prevalent, accounting for approximately 63% of all infections. The virulence capsular types K10, K136, and K2 were present in 16, 13, and 8% of the isolates, respectively. Phylogenomic analysis based on virtual genome fingerprints correlated with the MLST data. The phylogenomic reconstruction also denoted association between strains with a higher abundance of virulence genes and virulent serotypes compared to strains that do not possess these traits. This study highlights the value of whole-genomic sequencing in the surveillance of virulence attributes among clinical K. pneumoniae strains.

Prolonged drought imparts lasting compositional changes to the rice root microbiome

Microbial symbioses can mitigate drought stress in crops but harnessing these beneficial interactions will require an in-depth understanding of root microbiome responses to drought cycles. Here, by detailed temporal characterization of root-associated microbiomes of rice plants during drought stress and recovery, we find that endosphere communities remained compositionally altered after rewatering, with prolonged droughts leading to decreased resilience. Several endospheric Actinobacteria were significantly enriched during drought and for weeks after rewatering. Notably, the most abundant endosphere taxon during this period was a Streptomyces, and a corresponding isolate promoted root growth. Additionally, drought stress disrupted the temporal dynamics of late-colonizing microorganisms, permanently altering the normal successional trends of root microbiota. These findings reveal that severe drought results in enduring impacts on rice root microbiomes, including enrichment of taxonomic groups that could shape the recovery response of the host, and have implications relevant to drought protection strategies using root microbiota.

A comparative analysis of two unrelated outbreaks in Latvia and Australia of acquired idiopathic megaesophagus in dogs fed two brands of commercial dry dog foods: 398 cases (2014-2018)

CASE DESCRIPTION

In Latvia in 2014, acquired idiopathic megaesophagus (AIME) was observed in increased numbers of dogs that consumed varieties of 1 brand of dog food. Within 2 years, 253 dogs were affected. In Australia in November 2017, 6 working dogs that consumed 1 diet of another brand of dog food developed AIME. In total, 145 Australian dogs were affected.

CLINICAL FINDINGS

AIME was diagnosed predominantly in large-breed male dogs (> 25 kg [55 lb]). Regurgitation, weight loss, and occasionally signs consistent with aspiration pneumonia (coughing, dyspnea, or fever) were noted. Most Latvian dogs had mild to severe peripheral polyneuropathies as evidenced by laryngeal paralysis, dysphonia, weakness, and histopathologic findings consistent with distal axonopathy. In Australian dogs, peripheral polyneuropathies were not identified, and histopathologic findings suggested that the innervation of the esophagus and pharynx was disrupted locally, although limited samples were available.

TREATMENT AND OUTCOME

Investigations in both countries included clinical, epidemiological, neuropathologic, and case-control studies. Strong associations between the dog foods and the presence of AIME were confirmed; however, toxicological analyses did not identify a root cause. In Latvia, the implicated dietary ingredients and formulations were unknown, whereas in Australia, extensive investigations were conducted into the food, its ingredients, the supply chain, and the manufacturing facilities, but a cause was not identified.

CLINICAL RELEVANCE

A panel of international multidisciplinary experts concluded that the cause of AIME in both outbreaks was likely multifactorial, with the possibility of individualized sensitivities. Without a sentinel group, the outbreak in Australia may not have been recognized for months to years, as happened in Latvia. A better surveillance system for early identification of pet illnesses, including those associated with pet foods, is needed.

Analysis of SARS-CoV-2 genomic epidemiology reveals disease transmission coupled to variant emergence and allelic variation

The spread of SARS-CoV-2 created a pandemic crisis with > 150,000 cumulative cases in > 65 countries within a few months. The reproductive number (R) is a metric to estimate the transmission of a pathogen during an outbreak. Preliminary published estimates were based on the initial outbreak in China. Whole genome sequences (WGS) analysis found mutational variations in the viral genome; however, previous comparisons failed to show a direct relationship between viral genome diversity, transmission, and the epidemic severity. COVID-19 incidences from different countries were modeled over the epidemic curve. Estimates of the instantaneous R (Wallinga and Teunis method) with a short and standard serial interval were done. WGS were used to determine the populations genomic variation and that underpinned creation of the pathogen genome identity (GENI) score, which was merged with the outbreak curve in four distinct phases. Inference of transmission time was based on a mutation rate of 2 mutations/month. R estimates revealed differences in the transmission and variable infection dynamics between and within outbreak progression for each country examined. Outside China, our R estimates observed propagating dynamics indicating that other countries were poised to move to the takeoff and exponential stages. Population density and local temperatures had no clear relationship to the outbreak progression. Integration of incidence data with the GENI score directly predicted increases in cases as the genome variation increased that led to new variants. Integrating the outbreak curve, dynamic R, and SNP variation found a direct association between increasing cases and transmission genome evolution. By defining the epidemic curve into four stages and integrating the instantaneous country-specific R with the GENI score, we directly connected changes in individual outbreaks based on changes in the virus genome via SNPs. This resulted in the ability to forecast potential increases in cases as well as mutations that may defeat PCR screening and the infection process. By using instantaneous R estimations and WGS, outbreak dynamics were defined to be linked to viral mutations, indicating that WGS, as a surveillance tool, is required to predict shifts in each outbreak that will provide actionable decision making information. Integrating epidemiology with genome sequencing and modeling allows for evidence-based disease outbreak tracking with predictive therapeutically valuable insights in near real time.

Novel LC-MS-TOF method to detect and quantify ascorbic and uric acid simultaneously in different biological matrices

Ascorbic acid (AA) and uric acid (UA) are known as two of the major antioxidants in biological fluids. We report a novel liquid chromatography-mass spectrometry with time-of-flight (LC-MS-TOF) method for the simultaneous quantification of ascorbic and uric acids using MPA, antioxidant solution and acetonitrile as a protein precipitating agent. Both compounds were separated from interferences using a reverse phase C18 column with water and acetonitrile gradient elution (both with formic acid) and identified and quantified by MS in the negative ESI mode. Isotope labeled internal standards were also added to ensure the accuracy of the measures. The method was validated for exhaled breath condensate (EBC), nasal lavage (NL) and plasma samples by assessing selectivity, linearity, accuracy and precision, recovery and matrix effect and stability. Sample volumes below 250 µL were used and linear ranges were determined between 1 - 25 and 1 - 40 µg/mL for ascorbic and uric acid, respectively, for plasma samples, and between 0.05 - 5 (AA) and 0.05 - 7.5 (UA) µg/mL for EBC and NL samples. The new method was successfully applied to real samples from subjects that provided each of the studied matrices. Results showed higher amounts determined in plasma samples, with similar profiles for AA and UA in EBC and NL but at much lower concentrations.

Monitoring the microbiome for food safety and quality using deep shotgun sequencing

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species' viability from total RNA sequencing.

Phylogenetic and Biogeographic Patterns of Vibrio parahaemolyticus Strains from North America Inferred from Whole-Genome Sequence Data

Vibrio parahaemolyticus is the most common cause of seafood-borne illness reported in the United States. The draft genomes of 132 North American clinical and oyster V. parahaemolyticus isolates were sequenced to investigate their phylogenetic and biogeographic relationships. The majority of oyster isolate sequence types (STs) were from a single harvest location; however, four were identified from multiple locations. There was population structure along the Gulf and Atlantic Coasts of North America, with what seemed to be a hub of genetic variability along the Gulf Coast, with some of the same STs occurring along the Atlantic Coast and one shared between the coastal waters of the Gulf and those of Washington State. Phylogenetic analyses found nine well-supported clades. Two clades were composed of isolates from both clinical and oyster sources. Four were composed of isolates entirely from clinical sources, and three were entirely from oyster sources. Each single-source clade consisted of one ST. Some human isolates lack tdh, trh, and some type III secretion system (T3SS) genes, which are established virulence genes of V. parahaemolyticus Thus, these genes are not essential for pathogenicity. However, isolates in the monophyletic groups from clinical sources were enriched in several categories of genes compared to those from monophyletic groups of oyster isolates. These functional categories include cell signaling, transport, and metabolism. The identification of genes in these functional categories provides a basis for future in-depth pathogenicity investigations of V. parahaemolyticusIMPORTANCEVibrio parahaemolyticus is the most common cause of seafood-borne illness reported in the United States and is frequently associated with shellfish consumption. This study contributes to our knowledge of the biogeography and functional genomics of this species around North America. STs shared between the Gulf Coast and the Atlantic seaboard as well as Pacific waters suggest possible transport via oceanic currents or large shipping vessels. STs frequently isolated from humans but rarely, if ever, isolated from the environment are likely more competitive in the human gut than other STs. This could be due to additional functional capabilities in areas such as cell signaling, transport, and metabolism, which may give these isolates an advantage in novel nutrient-replete environments such as the human gut.

Molecular Epidemiology and Antimicrobial Resistance of Clostridioides difficile in Hospitalized Patients From Mexico

Clostridioides difficile is a global public health problem, which is a primary cause of antibiotic-associated diarrhea in humans. The emergence of hypervirulent and antibiotic-resistant strains is associated with the increased incidence and severity of the disease. There are limited studies on genomic characterization of C. difficile in Latin America. We aimed to learn about the molecular epidemiology and antimicrobial resistance in C. difficile strains from adults and children in hospitals of México. We studied 94 C. difficile isolates from seven hospitals in Mexico City from 2014 to 2018. Whole-genome sequencing (WGS) was used to determine the genotype and examine the toxigenic profiles. Susceptibility to antibiotics was determined by E-test. Multilocus sequence typing (MLST) was used to determine allelic profiles. Results identified 20 different sequence types (ST) in the 94 isolates, mostly clade 2 and clade 1. ST1 was predominant in isolates from adult and children. Toxigenic strains comprised 87.2% of the isolates that were combinations of tcdAB and cdtAB (tcdA+/tcdB+/cdtA+/cdtB+, followed by tcdA+/tcdB+/cdtA-/cdtB-, tcdA-/tcdB+/cdtA-/ cdtB-, and tcdA-/tcdB-/cdtA+/cdtB+). Toxin profiles were more diverse in isolates from children. All 94 isolates were susceptible to metronidazole and vancomycin, whereas a considerable number of isolates were resistant to clindamycin, fluroquinolones, rifampicin, meropenem, and linezolid. Multidrug-resistant isolates (≥3 antibiotics) comprised 65% of the isolates. The correlation between resistant genotypes and phenotypes was evaluated by the kappa test. Mutations in rpoB and rpoC showed moderate concordance with resistance to rifampicin and mutations in fusA substantial concordance with fusidic acid resistance. cfrE, a gene recently described in one Mexican isolate, was present in 65% of strains linezolid resistant, all ST1 organisms. WGS is a powerful tool to genotype and characterize virulence and antibiotic susceptibility patterns.

Identification of Nitrogen Fixation Genes in Lactococcus Isolated from Maize Using Population Genomics and Machine Learning

Sierra Mixe maize is a landrace variety from Oaxaca, Mexico, that utilizes nitrogen derived from the atmosphere via an undefined nitrogen fixation mechanism. The diazotrophic microbiota associated with the plant’s mucilaginous aerial root exudate composed of complex carbohydrates was previously identified and characterized by our group where we found 23 lactococci capable of biological nitrogen fixation (BNF) without containing any of the proposed essential genes for this trait (nifHDKENB). To determine the genes in Lactococcus associated with this phenotype, we selected 70 lactococci from the dairy industry that are not known to be diazotrophic to conduct a comparative population genomic analysis. This showed that the diazotrophic lactococcal genomes were distinctly different from the dairy isolates. Examining the pangenome followed by genome-wide association study and machine learning identified genes with the functions needed for BNF in the maize isolates that were absent from the dairy isolates. Many of the putative genes received an ‘unknown’ annotation, which led to the domain analysis of the 135 homologs. This revealed genes with molecular functions needed for BNF, including mucilage carbohydrate catabolism, glycan-mediated host adhesion, iron/siderophore utilization, and oxidation/reduction control. This is the first report of this pathway in this organism to underpin BNF. Consequently, we proposed a model needed for BNF in lactococci that plausibly accounts for BNF in the absence of the nif operon in this organism.

Diazotrophic bacteria from maize exhibit multifaceted plant growth promotion traits in multiple hosts

Sierra Mixe maize is a geographically remote landrace variety grown on nitrogen-deficient fields in Oaxaca, Mexico that meets its nutritional requirements without synthetic fertilizer by associating with free-living diazotrophs comprising the microbiota of its aerial root mucilage. We selected nearly 500 diazotrophic (N2-fixing) bacteria isolated from Sierra Mixe maize mucilage and sequenced their genomes. Comparative genomic analysis demonstrated that isolates represented diverse genera and composed three major diazotrophic groups based on nitrogen fixation gene content. In addition to nitrogen fixation, we examined deamination of 1-amino-1-cyclopropanecarboxylic acid, biosynthesis of indole-3-acetic acid, and phosphate solubilization as alternative mechanisms of direct plant growth promotion (PGP). Genome mining showed that isolates of all diazotrophic groups possessed marker genes for multiple mechanisms of direct plant growth promotion (PGP). Implementing in vitro assays corroborated isolate genotypes by measuring each isolate's potential to confer the targeted PGP traits and revealed phenotypic variation among isolates based on diazotrophic group assignment. Investigating the ability of mucilage diazotrophs to confer PGP by direct inoculation of clonally propagated potato plants in planta led to the identification of 16 bio-stimulant candidates. Conducting nitrogen-stress greenhouse experiments demonstrated that potato inoculation with a synthetic community of bio-stimulant candidates, as well as with its individual components, resulted in PGP phenotypes. We further demonstrated that one diazotrophic isolate conferred PGP to a conventional maize variety under nitrogen-stress in the greenhouse. These results indicate that, while many diazotrophic isolates from Sierra Mixe maize possessed genotypes and in vitro phenotypes for targeted PGP traits, a subset of these organisms promoted the growth of potato and conventional maize, potentially through the use of multiple promotion mechanisms.

Biological Machine Learning Combined with Campylobacter Population Genomics Reveals Virulence Gene Allelic Variants Cause Disease

Highly dimensional data generated from bacterial whole-genome sequencing is providing an unprecedented scale of information that requires an appropriate statistical analysis framework to infer biological function from populations of genomes. The application of genome-wide association study (GWAS) methods is an appropriate framework for bacterial population genome analysis that yields a list of candidate genes associated with a phenotype, but it provides an unranked measure of importance. Here, we validated a novel framework to define infection mechanism using the combination of GWAS, machine learning, and bacterial population genomics that ranked allelic variants that accurately identified disease. This approach parsed a dataset of 1.2 million single nucleotide polymorphisms (SNPs) and indels that resulted in an importance ranked list of associated alleles of porA in Campylobacter jejuni using spatiotemporal analysis over 30 years. We validated this approach using previously proven laboratory experimental alleles from an in vivo guinea pig abortion model. This framework, termed µPathML, defined intestinal and extraintestinal groups that have differential allelic porA variants that cause abortion. Divergent variants containing indels that defeated automated annotation were rescued using biological context and knowledge that resulted in defining rare, divergent variants that were maintained in the population over two continents and 30 years. This study defines the capability of machine learning coupled with GWAS and population genomics to simultaneously identify and rank alleles to define their role in infectious disease mechanisms.

Insular Microbiogeography: Three Pathogens as Exemplars

Traditional taxonomy in biology assumes that life is organized in a simple tree. Attempts to classify microorganisms in this way in the genomics era led microbiologists to look for finite sets of 'core' genes that uniquely group taxa as clades in the tree. However, the diversity revealed by large-scale whole genome sequencing is calling into question the long-held model of a hierarchical tree of life, which leads to questioning of the definition of a species. Large-scale studies of microbial genome diversity reveal that the cumulative number of new genes discovered increases with the number of genomes studied as a power law and subsequently leads to the lack of evidence for a unique core genome within closely related organisms. Sampling 'enough' new genomes leads to the discovery of a replacement or alternative to any gene. This power law behaviour points to an underlying self-organizing critical process that may be guided by mutation and niche selection. Microbes in any particular niche exist within a local web of organism interdependence known as the microbiome. The same mechanism that underpins the macro-ecological scaling first observed by MacArthur and Wilson also applies to microbial communities. Recent metagenomic studies of a food microbiome demonstrate the diverse distribution of community members, but also genotypes for a single species within a more complex community. Collectively, these results suggest that traditional taxonomic classification of bacteria could be replaced with a quasispecies model. This model is commonly accepted in virology and better describes the diversity and dynamic exchange of genes that also hold true for bacteria. This model will enable microbiologists to conduct population-scale studies to describe microbial behaviour, as opposed to a single isolate as a representative.

Nitrogen fixation in a landrace of maize is supported by a mucilage-associated diazotrophic microbiota

Plants are associated with a complex microbiota that contributes to nutrient acquisition, plant growth, and plant defense. Nitrogen-fixing microbial associations are efficient and well characterized in legumes but are limited in cereals, including maize. We studied an indigenous landrace of maize grown in nitrogen-depleted soils in the Sierra Mixe region of Oaxaca, Mexico. This landrace is characterized by the extensive development of aerial roots that secrete a carbohydrate-rich mucilage. Analysis of the mucilage microbiota indicated that it was enriched in taxa for which many known species are diazotrophic, was enriched for homologs of genes encoding nitrogenase subunits, and harbored active nitrogenase activity as assessed by acetylene reduction and ¹⁵N₂ incorporation assays. Field experiments in Sierra Mixe using ¹⁵N natural abundance or ¹⁵N-enrichment assessments over 5 years indicated that atmospheric nitrogen fixation contributed 29%–82% of the nitrogen nutrition of Sierra Mixe maize.

Nitrogen is an essential nutrient for plants, and for many nonlegume crops, the requirement for nitrogen is primarily met by the use of inorganic fertilizers. These fertilizers are produced from fossil fuel by energy-intensive processes that are estimated to use 1% to 2% of the total global energy supply and produce an equivalent share of greenhouse gases. Because maize (Zea mays L.) is a significant recipient of nitrogen fertilization, a research goal for decades has been to identify or engineer mechanisms for biological fixation of atmospheric nitrogen in association with this crop. We hypothesized that isolated indigenous landraces of maize grown using traditional practices with little or no fertilizer might have evolved strategies to improve plant performance under low-nitrogen nutrient conditions. Here, we show that for one such maize landrace grown in nitrogen-depleted fields near Oaxaca, Mexico, 29%–82% of the plant nitrogen is derived from atmospheric nitrogen. High levels of nitrogen fixation are supported, at least in part, by the abundant production of a sugar-rich mucilage associated with aerial roots that provides a home to a complex nitrogen-fixing microbiome.

Whole Cell Cross-Linking to Discover Host-Microbe Protein Cognate Receptor/Ligand Pairs

Bacterial surface ligands mediate interactions with the host cell during association that determines the specific outcome for the host–microbe association. The association begins with receptors on the host cell binding ligands on the microbial cell to form a partnership that initiates responses in both cells. Methods to determine the specific cognate partnerships are lacking. Determining these molecular interactions between the host and microbial surfaces are difficult, yet crucial in defining biologically important events that are triggered during association of the microbiome, and critical in defining the initiating signal from the host membrane that results in pathology or commensal association. In this study, we designed an approach to discover cognate host–microbe receptor/ligand pairs using a covalent cross-linking strategy with whole cells. Protein/protein cross-linking occurred when the interacting molecules were within 9–12 Å, allowing for identification of specific pairs of proteins from the host and microbe that define the molecular interaction during association. To validate the method three different bacteria with three previously known protein/protein partnerships were examined. The exact interactions were confirmed and led to discovery of additional partnerships that were not recognized as cognate partners, but were previously reported to be involved in bacterial interactions. Additionally, three unknown receptor/ligand partners were discovered and validated with in vitro infection assays by blocking the putative host receptor and deleting the bacterial ligand. Subsequently, Salmonella enterica sv. Typhimurium was cross-linked to differentiated colonic epithelial cells (caco-2) to discover four previously unknown host receptors bound to three previously undefined host ligands for Salmonella. This approach resulted in a priori discovery of previously unknown and biologically important molecules for host/microbe association that were casually reported to mediate bacterial invasion. The whole cell cross-linking approach promises to enable discovery of possible targets to modulate interaction of the microbiome with the host that are important in infection and commensalism, both of with initiate a host response.

Comparative analysis of Campylobacter isolates from wild birds and chickens using MALDI-TOF MS, biochemical testing, and DNA sequencing

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was compared to conventional biochemical testing methods and nucleic acid analyses (16S rDNA sequencing, hippurate hydrolysis gene testing, whole genome sequencing [WGS]) for species identification of Campylobacter isolates obtained from chickens ( Gallus gallus domesticus, n = 8), American crows ( Corvus brachyrhynchos, n = 17), a mallard duck ( Anas platyrhynchos, n = 1), and a western scrub-jay ( Aphelocoma californica, n = 1). The test results for all 27 isolates were in 100% agreement between MALDI-TOF MS, the combined results of 16S rDNA sequencing, and the hippurate hydrolysis gene PCR ( p = 0.0027, kappa = 1). Likewise, the identifications derived from WGS from a subset of 14 isolates were in 100% agreement with the MALDI-TOF MS identification. In contrast, biochemical testing misclassified 5 isolates of C. jejuni as C. coli, and 16S rDNA sequencing alone was not able to differentiate between C. coli and C. jejuni for 11 sequences ( p = 0.1573, kappa = 0.0857) when compared to MALDI-TOF MS and WGS. No agreement was observed between MALDI-TOF MS dendrograms and the phylogenetic relationships revealed by rDNA sequencing or WGS. Our results confirm that MALDI-TOF MS is a fast and reliable method for identifying Campylobacter isolates to the species level from wild birds and chickens, but not for elucidating phylogenetic relationships among Campylobacter isolates.

Exhaled breath condensate methods adapted from human studies using longitudinal metabolomics for predicting early health alterations in dolphins

Monitoring health conditions is essential to detect early asymptomatic stages of a disease. To achieve this, blood, urine and breath samples are commonly used as a routine clinical diagnostic. These samples offer the opportunity to detect specific metabolites related to diseases and provide a better understanding of their development. Although blood samples are commonly used routinely to monitor health, the implementation of a relatively noninvasive technique, such as exhaled breath condensate (EBC) analysis, may further benefit the well-being of both humans and other animals. EBC analysis can be used to track possible physical or biochemical alterations caused by common diseases of the bottlenose dolphin (Tursiops truncatus), such as infections or inflammatory-mediated processes. We have used an untargeted metabolomic method with liquid chromatography-mass spectrometry analysis of EBC samples to determine biomarkers related to disease development. In this study, five dolphins under human care were followed up for 1 year. We collected paired blood, physical examination information, and EBC samples. We then statistically correlated this information to predict specific health alterations. Three dolphins provided promising case study information about biomarkers related to cutaneous infections, respiratory infections, dental disease, or hormonal changes (pregnancy). The use of complementary liquid chromatography platforms, with hydrophilic interaction chromatography and reverse-phased columns, allowed us to detect a wide spectrum of EBC biomarker compounds that could be related to these health alterations. Moreover, these two analytical techniques not only provided complementary metabolite information but in both cases they also provided promising diagnostic information for these health conditions. Graphical abstract Collection of the exhaled condensed breath from a bottlenose dolphin from U.S. Navy Marine Mammal Program (MMP).

SigTree: A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.

Analytical methodologies for broad metabolite coverage of exhaled breath condensate

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

Automation of PacBio SMRTbell NGS library preparation for bacterial genome sequencing

Background

The PacBio RS II provides for single molecule, real-time DNA technology to sequence genomes and detect DNA modifications. The starting point for high-quality sequence production is high molecular weight genomic DNA. To automate the library preparation process, there must be high-throughput methods in place to assess the genomic DNA, to ensure the size and amounts of the sheared DNA fragments and final library.

Findings

The library construction automation was accomplished using the Agilent NGS workstation with Bravo accessories for heating, shaking, cooling, and magnetic bead manipulations for template purification.

The quality control methods from gDNA input to final library using the Agilent Bioanalyzer System and Agilent TapeStation System were evaluated.

Conclusions

Automated protocols of PacBio 10 kb library preparation produced libraries with similar technical performance to those generated manually. The TapeStation System proved to be a reliable method that could be used in a 96-well plate format to QC the DNA equivalent to the standard Bioanalyzer System results. The DNA Integrity Number that is calculated in the TapeStation System software upon analysis of genomic DNA is quite helpful to assure that the starting genomic DNA is not degraded. In this respect, the gDNA assay on the TapeStation System is preferable to the DNA 12000 assay on the Bioanalyzer System, which cannot run genomic DNA, nor can the Bioanalyzer work directly from the 96-well plates.

Fallacy of the Unique Genome: Sequence Diversity within Single Helicobacter pylori Strains

Many bacterial genomes are highly variable but nonetheless are typically published as a single assembled genome. Experiments tracking bacterial genome evolution have not looked at the variation present at a given point in time. Here, we analyzed the mouse-passaged Helicobacter pylori strain SS1 and its parent PMSS1 to assess intra- and intergenomic variability. Using high sequence coverage depth and experimental validation, we detected extensive genome plasticity within these H. pylori isolates, including movement of the transposable element IS607, large and small inversions, multiple single nucleotide polymorphisms, and variation in cagA copy number. The cagA gene was found as 1 to 4 tandem copies located off the cag island in both SS1 and PMSS1; this copy number variation correlated with protein expression. To gain insight into the changes that occurred during mouse adaptation, we also compared SS1 and PMSS1 and observed 46 differences that were distinct from the within-genome variation. The most substantial was an insertion in cagY, which encodes a protein required for a type IV secretion system function. We detected modifications in genes coding for two proteins known to affect mouse colonization, the HpaA neuraminyllactose-binding protein and the FutB α-1,3 lipopolysaccharide (LPS) fucosyltransferase, as well as genes predicted to modulate diverse properties. In sum, our work suggests that data from consensus genome assemblies from single colonies may be misleading by failing to represent the variability present. Furthermore, we show that high-depth genomic sequencing data of a population can be analyzed to gain insight into the normal variation within bacterial strains.IMPORTANCE Although it is well known that many bacterial genomes are highly variable, it is nonetheless traditional to refer to, analyze, and publish "the genome" of a bacterial strain. Variability is usually reduced ("only sequence from a single colony"), ignored ("just publish the consensus"), or placed in the "too-hard" basket ("analysis of raw read data is more robust"). Now that whole-genome sequences are regularly used to assess virulence and track outbreaks, a better understanding of the baseline genomic variation present within single strains is needed. Here, we describe the variability seen in typical working stocks and colonies of pathogen Helicobacter pylori model strains SS1 and PMSS1 as revealed by use of high-coverage mate pair next-generation sequencing (NGS) and confirmed by traditional laboratory techniques. This work demonstrates that reliance on a consensus assembly as "the genome" of a bacterial strain may be misleading.

Human breath metabolomics using an optimized non-invasive exhaled breath condensate sampler

Exhaled breath condensate (EBC) analysis is a developing field with tremendous promise to advance personalized, non-invasive health diagnostics as new analytical instrumentation platforms and detection methods are developed. Multiple commercially-available and researcher-built experimental samplers are reported in the literature. However, there is very limited information available to determine an effective breath sampling approach, especially regarding the dependence of breath sample metabolomic content on the collection device design and sampling methodology. This lack of an optimal standard procedure results in a range of reported results that are sometimes contradictory. Here, we present a design of a portable human EBC sampler optimized for collection and preservation of the rich metabolomic content of breath. The performance of the engineered device is compared to two commercially available breath collection devices: the RTube^™ and TurboDECCS. A number of design and performance parameters are considered, including: condenser temperature stability during sampling, collection efficiency, condenser material choice, and saliva contamination in the collected breath samples. The significance of the biological content of breath samples, collected with each device, is evaluated with a set of mass spectrometry methods and was the primary factor for evaluating device performance. The design includes an adjustable mass-size threshold for aerodynamic filtering of saliva droplets from the breath flow. Engineering an inexpensive device that allows efficient collection of metalomic-rich breath samples is intended to aid further advancement in the field of breath analysis for non-invasive health diagnostic. EBC sampling from human volunteers was performed under UC Davis IRB protocol 63701-3 (09/30/2014-07/07/2017).

Salmonella Typhimurium Enzymatically Landscapes the Host Intestinal Epithelial Cell (IEC) Surface Glycome to Increase Invasion

Although gut host-pathogen interactions are glycan-mediated processes, few details are known about the participating structures. Here we employ high-resolution mass spectrometric profiling to comprehensively identify and quantitatively measure the exact modifications of native intestinal epithelial cell surface N-glycans induced by S. typhimurium infection. Sixty minutes postinfection, select sialylated structures showed decreases in terms of total number and abundances. To assess the effect of cell surface mannosylation, we selectively rerouted glycan expression on the host using the alpha-mannosidase inhibitor, kifunensine, toward overexpression of high mannose. Under these conditions, internalization of S. typhimurium significantly increased, demonstrating that bacteria show preference for particular structures. Finally, we developed a novel assay to measure membrane glycoprotein turnover rates, which revealed that glycan modifications occur by bacterial enzyme activity rather than by host-derived restructuring strategies. This study is the first to provide precise structural information on how host N-glycans are altered to support S. typhimurium invasion.

Enhanced non-invasive respiratory sampling from bottlenose dolphins for breath metabolomics measurements

Chemical analysis of exhaled breath metabolites is an emerging alternative to traditional clinical testing for many physiological conditions. The main advantage of breath analysis is its inherent non-invasive nature and ease of sample collection. Therefore, there exists a great interest in further development of this method for both humans and animals. The physiology of cetaceans is exceptionally well suited for breath analysis due to their explosive breathing behavior and respiratory tract morphology. At the present time, breath analysis in cetaceans has very limited practical applications, in large part due to lack of widely adopted sampling device(s) and methodologies that are well-standardized. Here, we present an optimized design and the operating principles of a portable apparatus for reproducible collection of exhaled breath condensate from small cetaceans, such as bottlenose dolphins (Tursiops truncatus). The device design is optimized to meet two criteria: standardized collection and preservation of information-rich metabolomic content of the biological sample, and animal comfort and ease of breath sample collection. The intent is to furnish a fully-benchmarked technology that can be widely adopted by researchers and conservationists to spur further developments of breath analysis applications for marine mammal health assessments.

Gut microbiota-produced succinate promotes C. difficile infection after antibiotic treatment or motility disturbance

Clostridium difficile is a leading cause of antibiotic-associated diarrhea. The mechanisms underlying C. difficile expansion after microbiota disturbance are just emerging. We assessed the gene expression profile of C. difficile within the intestine of gnotobiotic mice to identify genes regulated in response to either dietary or microbiota compositional changes. In the presence of the gut symbiont Bacteroides thetaiotaomicron, C. difficile induces a pathway that metabolizes the microbiota fermentation end-product succinate to butyrate. The low concentration of succinate present in the microbiota of conventional mice is transiently elevated upon antibiotic treatment or chemically induced intestinal motility disturbance, and C. difficile exploits this succinate spike to expand in the perturbed intestine. A C. difficile mutant compromised in succinate utilization is at a competitive disadvantage during these perturbations. Understanding the metabolic mechanisms involved in microbiota-C. difficile interactions may help to identify approaches for the treatment and prevention of C. difficile-associated diseases.

Genomic epidemiology of Salmonella enterica serotype Enteritidis based on population structure of prevalent lineages

Major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

Salmonella enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis. Its low genetic diversity, measured by fingerprinting methods, has made subtyping a challenge. We used whole-genome sequencing to characterize 125 S. enterica Enteritidis and 3 S. enterica serotype Nitra strains. Single-nucleotide polymorphisms were filtered to identify 4,887 reliable loci that distinguished all isolates from each other. Our whole-genome single-nucleotide polymorphism typing approach was robust for S. enterica Enteritidis subtyping with combined data for different strains from 2 different sequencing platforms. Five major genetic lineages were recognized, which revealed possible patterns of geographic and epidemiologic distribution. Analyses on the population dynamics and evolutionary history estimated that major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction

Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Gastrointestinal microbes interact with canine adipose-derived mesenchymal stem cells in vitro and enhance immunomodulatory functions

Mesenchymal stem cells (MSCs) are somatic, multipotent stromal cells with potent immunomodulatory and regenerative properties. Although MSCs have pattern recognition receptors and are modulated by Toll-like receptor ligands, MSC-microbial interactions are poorly defined. The objectives of this study were to determine the effect of bacterial association on MSC function. We hypothesized that gastrointestinal bacteria associate with MSCs and alter their immunomodulatory properties. The effect of MSC-microbial interactions on MSC morphology, viability, proliferation, migration, and immunomodulatory functions was investigated. MSCs associated with a remarkable array of enteric pathogens and commensal bacteria. MSC interactions with two model organisms, the pathogen Salmonella typhimurium and the probiotic Lactobacillus acidophilus, were further investigated. While ST readily invaded MSCs, LB adhered to the MSC plasma membrane. Neither microbe induced MSC death, degeneration, or diminished proliferation. Microbial association did not upregulate MHC-II, CD80/86, or CD1 expression. MSC-microbial interaction significantly increased transcription of key immunomodulatory genes, including COX2, IL6, and IL8, coupled with significantly increased prostaglandin E2 (PGE2), interleukin (IL)6, and IL8 secretion. MSC-ST coincubation resulted in increased MSC expression of CD54, and significant augmentation of MSC inhibition of mitogen-induced T-cell proliferation. T-cell proliferation was partially restored when PGE2 secretion was blocked from ST-primed MSCs. MSC-microbe interactions have a profound effect on MSC function and may be pivotal in a variety of clinical settings where MSCs are being explored as potential therapeutics in the context of microbial communities, such as Crohn's disease, chronic nonhealing wounds, and sepsis.

Exploring bacterial epigenomics in the next-generation sequencing era: a new approach for an emerging frontier

Epigenetics has an important role for the success of foodborne pathogen persistence in diverse host niches. Substantial challenges exist in determining DNA methylation to situation-specific phenotypic traits. DNA modification, mediated by restriction-modification systems, functions as an immune response against antagonistic external DNA, and bacteriophage-acquired methyltransferases (MTase) and orphan MTases - those lacking the cognate restriction endonuclease - facilitate evolution of new phenotypes via gene expression modulation via DNA and RNA modifications, including methylation and phosphorothioation. Recent establishment of large-scale genome sequencing projects will result in a significant increase in genome availability that will lead to new demands for data analysis including new predictive bioinformatics approaches that can be verified with traditional scientific rigor. Sequencing technologies that detect modification coupled with mass spectrometry to discover new adducts is a powerful tactic to study bacterial epigenetics, which is poised to make novel and far-reaching discoveries that link biological significance and the bacterial epigenome.

Cross-talk between E. coli strains and a human colorectal adenocarcinoma-derived cell line

Although there is great interest in the specific mechanisms of how gut microbiota modulate the biological processes of the human host, the extent of host-microbe interactions and the bacteria-specific metabolic activities for survival in the co-evolved gastrointestinal environment remain unclear. Here, we demonstrate a comprehensive comparison of the host epithelial response induced by either a pathogenic or commensal strain of Escherichia coli using a multi-omics approach. We show that Caco-2 cells incubated with E. coli display an activation of defense response genes associated with oxidative stress. Indeed, in the bacteria co-culture system, the host cells experience an altered environment compared with the germ-free system that includes reduced pH, depletion of major energy substrates, and accumulation of fermentation by-products. Measurement of intracellular Caco-2 cell metabolites revealed a significantly increased lactate concentration, as well as changes in TCA cycle intermediates. Our results will lead to a deeper understanding of acute microbial-host interactions.

Insulin receptor substrate signaling suppresses neonatal autophagy in the heart

The induction of autophagy in the mammalian heart during the perinatal period is an essential adaptation required to survive early neonatal starvation; however, the mechanisms that mediate autophagy suppression once feeding is established are not known. Insulin signaling in the heart is transduced via insulin and IGF-1 receptors (IGF-1Rs). We disrupted insulin and IGF-1R signaling by generating mice with combined cardiomyocyte-specific deletion of Irs1 and Irs2. Here we show that loss of IRS signaling prevented the physiological suppression of autophagy that normally parallels the postnatal increase in circulating insulin. This resulted in unrestrained autophagy in cardiomyocytes, which contributed to myocyte loss, heart failure, and premature death. This process was ameliorated either by activation of mTOR with aa supplementation or by genetic suppression of autophagic activation. Loss of IRS1 and IRS2 signaling also increased apoptosis and precipitated mitochondrial dysfunction, which were not reduced when autophagic flux was normalized. Together, these data indicate that in addition to prosurvival signaling, insulin action in early life mediates the physiological postnatal suppression of autophagy, thereby linking nutrient sensing to postnatal cardiac development.

Microbiota-liberated host sugars facilitate post-antibiotic expansion of enteric pathogens

The human intestine, colonized by a dense community of resident microbes, is a frequent target of bacterial pathogens. Undisturbed, this intestinal microbiota provides protection from bacterial infections. Conversely, disruption of the microbiota with oral antibiotics often precedes the emergence of several enteric pathogens^1–4. How pathogens capitalize upon the failure of microbiota-afforded protection is largely unknown. Here we show that two antibiotic-associated pathogens, Salmonella typhimurium and Clostridium difficile, employ a common strategy of catabolizing microbiota-liberated mucosal carbohydrates during their expansion within the gut. S. typhimurium accesses fucose and sialic acid within the lumen of the gut in a microbiota-dependent manner, and genetic ablation of the respective catabolic pathways reduces its competitiveness in vivo. Similarly, C. difficile expansion is aided by microbiota-induced elevation of sialic acid levels in vivo. Colonization of gnotobiotic mice with a sialidase-deficient mutant of the model gut symbiont Bacteroides thetaiotaomicron (Bt) reduces free sialic acid levels resulting in a downregulation of C. difficile’s sialic acid catabolic pathway and impaired expansion. These effects are reversed by exogenous dietary administration of free sialic acid. Furthermore, antibiotic treatment of conventional mice induces a spike in free sialic acid and mutants of both Salmonella and C. difficile that are unable to catabolize sialic acid exhibit impaired expansion. These data show that antibiotic-induced disruption of the resident microbiota and subsequent alteration in mucosal carbohydrate availability are exploited by these two distantly related enteric pathogens in a similar manner. This insight suggests new possibilities for therapeutic approaches for preventing diseases caused by antibiotic-associated pathogens.

Dissecting the role of milk components on gut microbiota composition

The composition of human milk is tailored to contribute to the development of the gastrointestinal (GI) tract of newborns and infants. Importantly, human milk contains the antimicrobial compounds lysozyme and lactoferrin that are thought to contribute to the formation of a health-promoting microbiota. As these protective factors are lacking in the milk of dairy animals, we genetically engineered goats expressing human lysozyme in their milk and have recently reported a new animal model to dissect out the role of milk components on gut microbiota formation. Using the pig as a more human-relevant animal model, we demonstrated that consumption of lysozyme-rich milk enriched the abundance of bacteria associated with GI health and decreased those associated with disease, much like human milk. This work demonstrated that the pig is a valid animal model for gut microbiome studies on the effects of dietary components on microbiota composition, host-microbe interactions and state of the intestine.

Genetic loss of insulin receptors worsens cardiac efficiency in diabetes

AIMS

To determine the contribution of insulin signaling versus systemic metabolism to metabolic and mitochondrial alterations in type 1 diabetic hearts and test the hypothesis that antecedent mitochondrial dysfunction contributes to impaired cardiac efficiency (CE) in diabetes.

METHODS AND RESULTS

Control mice (WT) and mice with cardiomyocyte-restricted deletion of insulin receptors (CIRKO) were rendered diabetic with streptozotocin (WT-STZ and CIRKO-STZ, respectively), non-diabetic controls received vehicle (citrate buffer). Cardiac function was determined by echocardiography; myocardial metabolism, oxygen consumption (MVO(2)) and CE were determined in isolated perfused hearts; mitochondrial function was determined in permeabilized cardiac fibers and mitochondrial proteomics by liquid chromatography mass spectrometry. Pyruvate supported respiration and ATP synthesis were equivalently reduced by diabetes and genotype, with synergistic impairment in ATP synthesis in CIRKO-STZ. In contrast, fatty acid delivery and utilization was increased by diabetes irrespective of genotype, but not in non-diabetic CIRKO. Diabetes and genotype synergistically increased MVO(2) in CIRKO-STZ, leading to reduced CE. Irrespective of diabetes, genotype impaired ATP/O ratios in mitochondria exposed to palmitoyl carnitine, consistent with mitochondrial uncoupling. Proteomics revealed reduced content of fatty acid oxidation proteins in CIRKO mitochondria, which were induced by diabetes, whereas tricarboxylic acid cycle and oxidative phosphorylation proteins were reduced both in CIRKO mitochondria and by diabetes.

CONCLUSIONS

Deficient insulin signaling and diabetes mediate distinct effects on cardiac mitochondria. Antecedent loss of insulin signaling markedly impairs CE when diabetes is induced, via mechanisms that may be secondary to mitochondrial uncoupling and increased FA utilization.