Characterization of an Arginine Decarboxylase from Streptococcus pneumoniae by Ultrahigh-Performance Liquid Chromatography-Tandem Mass Spectrometry.

Polyamines are polycations derived from amino acids that play an important role in proliferation and growth in almost all living cells. In Streptococcus pneumoniae (the pneumococcus), modulation of polyamine metabolism not only plays an important regulatory role in central metabolism, but also impacts virulence factors such as the capsule and stress responses that affect survival in the host. However, functional annotation of enzymes from the polyamine biosynthesis pathways in the pneumococcus is based predominantly on computational prediction. In this study, we cloned SP_0166, predicted to be a pyridoxal-dependent decarboxylase, from the Orn/Lys/Arg family pathway in S. pneumoniae TIGR4 and expressed and purified the recombinant protein. We performed biochemical characterization of the recombinant SP_0166 and confirmed the substrate specificity. For polyamine analysis, we developed a simultaneous quantitative method using hydrophilic interaction liquid chromatography (HILIC)-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) without derivatization. SP_0166 has apparent Km, kcat, and kcat/Km values of 11.3 mM, 715,053 min-1, and 63,218 min-1 mM-1, respectively, with arginine as a substrate at pH 7.5. We carried out inhibition studies of SP_0166 enzymatic activity with arginine as a substrate using chemical inhibitors DFMO and DFMA. DFMO is an irreversible inhibitor of ornithine decarboxylase activity, while DFMA inhibits arginine decarboxylase activity. Our findings confirm that SP_0166 is inhibited by DFMA and DFMO, impacting agmatine production. The use of arginine as a substrate revealed that the synthesis of putrescine by agmatinase and N-carbamoylputrescine by agmatine deiminase were both affected and inhibited by DFMA. This study provides experimental validation that SP_0166 is an arginine decarboxylase in pneumococci.

Impact of Difluoromethylornithine and AMXT 1501 on Gene Expression and Capsule Regulation in Streptococcus pneumoniae.

Streptococcus pneumoniae (Spn), a Gram-positive bacterium, poses a significant threat to human health, causing mild respiratory infections to severe invasive conditions. Despite the availability of vaccines, challenges persist due to serotype replacement and antibiotic resistance, emphasizing the need for alternative therapeutic strategies. This study explores the intriguing role of polyamines, ubiquitous, small organic cations, in modulating virulence factors, especially the capsule, a crucial determinant of Spn's pathogenicity. Using chemical inhibitors, difluoromethylornithine (DFMO) and AMXT 1501, this research unveils distinct regulatory effects on the gene expression of the Spn D39 serotype in response to altered polyamine homeostasis. DFMO inhibits polyamine biosynthesis, disrupting pathways associated with glucose import and the interconversion of sugars. In contrast, AMXT 1501, targeting polyamine transport, enhances the expression of polyamine and glucose biosynthesis genes, presenting a novel avenue for regulating the capsule independent of glucose availability. Despite ample glucose availability, AMXT 1501 treatment downregulates the glycolytic pathway, fatty acid synthesis, and ATP synthase, crucial for energy production, while upregulating two-component systems responsible for stress management. This suggests a potential shutdown of energy production and capsule biosynthesis, redirecting resources towards stress management. Following DFMO and AMXT 1501 treatments, countermeasures, such as upregulation of stress response genes and ribosomal protein, were observed but appear to be insufficient to overcome the deleterious effects on capsule production. This study highlights the complexity of polyamine-mediated regulation in S. pneumoniae, particularly capsule biosynthesis. Our findings offer valuable insights into potential therapeutic targets for modulating capsules in a polyamine-dependent manner, a promising avenue for intervention against S. pneumoniae infections.

Predicting Salmonella MIC and Deciphering Genomic Determinants of Antibiotic Resistance and Susceptibility.

Salmonella spp., a leading cause of foodborne illness, is a formidable global menace due to escalating antimicrobial resistance (AMR). The evaluation of minimum inhibitory concentration (MIC) for antimicrobials is critical for characterizing AMR. The current whole genome sequencing (WGS)-based approaches for predicting MIC are hindered by both computational and feature identification constraints. We propose an innovative methodology called the "Genome Feature Extractor Pipeline" that integrates traditional machine learning (random forest, RF) with deep learning models (multilayer perceptron (MLP) and DeepLift) for WGS-based MIC prediction. We used a dataset from the National Antimicrobial Resistance Monitoring System (NARMS), comprising 4500 assembled genomes of nontyphoidal Salmonella, each annotated with MIC metadata for 15 antibiotics. Our pipeline involves the batch downloading of annotated genomes, the determination of feature importance using RF, Gini-index-based selection of crucial 10-mers, and their expansion to 20-mers. This is followed by an MLP network, with four hidden layers of 1024 neurons each, to predict MIC values. Using DeepLift, key 20-mers and associated genes influencing MIC are identified. The 10 most significant 20-mers for each antibiotic are listed, showcasing our ability to discern genomic features affecting Salmonella MIC prediction with enhanced precision. The methodology replaces binary indicators with k-mer counts, offering a more nuanced analysis. The combination of RF and MLP addresses the limitations of the existing WGS approach, providing a robust and efficient method for predicting MIC values in Salmonella that could potentially be applied to other pathogens.

Predicting foodborne pathogens and probiotics taxa within poultry-related microbiomes using a machine learning approach.

BACKGROUND: Microbiomes that can serve as an indicator of gut, intestinal, and general health of humans and animals are largely influenced by food consumed and contaminant bioagents. Microbiome studies usually focus on estimating the alpha (within sample) and beta (similarity/dissimilarity among samples) diversities. This study took a combinatorial approach and applied machine learning to microbiome data to predict the presence of disease-causing pathogens and their association with known/potential probiotic taxa. Probiotics are beneficial living microorganisms capable of improving the host organism's digestive system, immune function and ultimately overall health. Here, 16 S rRNA gene high-throughput Illumina sequencing of temporal pre-harvest (feces, soil) samples of 42 pastured poultry flocks (poultry in this entire work solely refers to chickens) from southeastern U.S. farms was used to generate the relative abundance of operational taxonomic units (OTUs) as machine learning input. Unique genera from the OTUs were used as predictors of the prevalence of foodborne pathogens (Salmonella, Campylobacter and Listeria) at different stages of poultry growth (START (2-4 weeks old), MID (5-7 weeks old), END (8-11 weeks old)), association with farm management practices and physicochemical properties. RESULT: While we did not see any significant associations between known probiotics and Salmonella or Listeria, we observed significant negative correlations between known probiotics (Bacillus and Clostridium) and Campylobacter at the mid-time point of sample collection. Our data indicates a negative correlation between potential probiotics and Campylobacter at both early and end-time points of sample collection. Furthermore, our model prediction shows that changes in farm operations such as how often the houses are moved on the pasture, age at which chickens are introduced to the pasture, diet composition and presence of other animals on the farm could favorably increase the abundance and activity of probiotics that could reduce Campylobacter prevalence. CONCLUSION: Integration of microbiome data with farm management practices using machine learning provided insights on how to reduce Campylobacter prevalence and transmission along the farm-to-fork continuum. Altering management practices to support proliferation of beneficial probiotics to reduce pathogen prevalence identified here could constitute a complementary method to the existing but ineffective interventions such as vaccination and bacteriophage cocktails usage. Study findings also corroborate the presence of bacterial genera such as Caloramator, DA101, Parabacteroides and Faecalibacterium as potential probiotics.

An ensemble learning approach to identify pastured poultry farm practice variables and soil constituents that promote Salmonella prevalence.

Animal sourced foods including contaminated poultry meat and eggs contribute to human non-typhoidal salmonellosis, a foodborne zoonosis. Prevalence of Salmonella in pastured poultry production systems can lead to contamination of the final product. Identification of farm practices that affect Salmonella prevalence is critical for implementing control measures to ensure the safety of these products. In this study, we developed predictive models based predominantly on deep learning approaches to identify key pre-harvest management variables (using soil and feces samples) in pastured poultry farms that contribute to Salmonella prevalence. Our ensemble approach utilizing five different machine learning techniques predicts that physicochemical parameters of the soil and feces (elements such as sodium (Na), zinc (Zn), potassium (K), copper (Cu)), electrical conductivity (EC), the number of years that the farms have been in use, and flock size significantly influence pre-harvest Salmonella prevalence. Egg source, feed type, breed, and manganese (Mn) levels in the soil/feces are other important variables identified to contribute to Salmonella prevalence on larger (≥3 flocks reared per year) farms, while pasture feed and soil carbon-to-nitrogen ratio are predicted to be important for smaller/hobby (<3 flocks reared per year) farms. Predictive models such as the ones described here are important for developing science-based control measures for Salmonella to reduce the environmental, animal, and public health impacts from these types of poultry production systems.

Preharvest Environmental and Management Drivers of Multidrug Resistance in Major Bacterial Zoonotic Pathogens in Pastured Poultry Flocks.

Due to nutritional benefits and perceived humane ways of treating the animals, the demand for antibiotic-free pastured poultry chicken has continued to be steadily rise. Despite the non-usage of antibiotics in pastured poultry broiler production, antibiotic resistance (AR) is reported in zoonotic poultry pathogens. However, factors that drive multidrug resistance (MDR) in pastured poultry are not well understood. In this study, we used machine learning and deep learning approaches to predict farm management practices and physicochemical properties of feces and soil that drive MDR in zoonotic poultry pathogens. Antibiotic use in agroecosystems is known to contribute to resistance. Evaluation of the development of resistance in environments that are free of antibiotics such as the all-natural, antibiotic-free, pastured poultry production systems described here is critical to understand the background AR in the absence of any selection pressure, i.e., basal levels of resistance. We analyzed 1635 preharvest (feces and soil) samples collected from forty-two pastured poultry flocks and eleven farms in the Southeastern United States. CDC National Antimicrobial Resistance Monitoring System guidelines were used to determine antimicrobial/multidrug resistance profiles of Salmonella, Listeria, and Campylobacter. A combination of two traditional machine learning (RandomForest and XGBoost) and three deep learning (Multi-layer Perceptron, Generative Adversarial Network, and Auto-Encoder) approaches identified critical farm management practices and environmental variables that drive multidrug resistance in poultry pathogens in broiler production systems that represents background resistance. This study enumerates management practices that contribute to AR and makes recommendations to potentially mitigate multidrug resistance and the prevalence of Salmonella and Listeria in pastured poultry.

Difluoromethylornithine (DFMO) and AMXT 1501 inhibit capsule biosynthesis in pneumococci.

Polyamines are small cationic molecules that have been linked to various cellular processes including replication, translation, stress response and recently, capsule regulation in Streptococcus pneumoniae (Spn, pneumococcus). Pneumococcal-associated diseases such as pneumonia, meningitis, and sepsis are some of the leading causes of death worldwide and capsule remains the principal virulence factor of this versatile pathogen. α-Difluoromethyl-ornithine (DFMO) is an irreversible inhibitor of the polyamine biosynthesis pathway catalyzed by ornithine decarboxylase and has a long history in modulating cell growth, polyamine levels, and disease outcomes in eukaryotic systems. Recent evidence shows that DFMO can also target arginine decarboxylation. Interestingly, DFMO-treated cells often escape polyamine depletion via increased polyamine uptake from extracellular sources. Here, we examined the potential capsule-crippling ability of DFMO and the possible synergistic effects of the polyamine transport inhibitor, AMXT 1501, on pneumococci. We characterized the changes in pneumococcal metabolites in response to DFMO and AMXT 1501, and also measured the impact of DFMO on amino acid decarboxylase activities. Our findings show that DFMO inhibited pneumococcal polyamine and capsule biosynthesis as well as decarboxylase activities, albeit, at a high concentration. AMXT 1501 at physiologically relevant concentration could inhibit both polyamine and capsule biosynthesis, however, in a serotype-dependent manner. In summary, this study demonstrates the utility of targeting polyamine biosynthesis and transport for pneumococcal capsule inhibition. Since targeting capsule biosynthesis is a promising way for the eradication of the diverse and pathogenic pneumococcal strains, future work will identify small molecules similar to DFMO/AMXT 1501, which act in a serotype-independent manner.

The Effect of Impaired Polyamine Transport on Pneumococcal Transcriptome.

Infections due to Streptococcus pneumoniae, a commensal in the nasopharynx, still claim a significant number of lives worldwide. Genome plasticity, antibiotic resistance, and limited serotype coverage of the available polysaccharide-based conjugate vaccines confounds therapeutic interventions to limit the spread of this pathogen. Pathogenic mechanisms that allow successful adaption and persistence in the host could be potential innovative therapeutic targets. Polyamines are ubiquitous polycationic molecules that regulate many cellular processes. We previously reported that deletion of polyamine transport operon potABCD, which encodes a putrescine/spermidine transporter (ΔpotABCD), resulted in an unencapsulated attenuated phenotype. Here, we characterize the transcriptome, metabolome, and stress responses of polyamine transport-deficient S. pneumoniae. Compared with the wild-type strain, the expression of genes involved in oxidative stress responses and the nucleotide sugar metabolism was reduced, while expression of genes involved in the Leloir, tagatose, and pentose phosphate pathways was higher in ΔpotABCD. A metabolic shift towards the pentose phosphate pathway will limit the synthesis of precursors of capsule polysaccharides. Metabolomics results show reduced levels of glutathione and pyruvate in the mutant. Our results also show that the potABCD operon protects pneumococci against hydrogen peroxide and nitrosative stress. Our findings demonstrate the importance of polyamine transport in pneumococcal physiology that could impact in vivo fitness. Thus, polyamine transport in pneumococci represents a novel target for therapeutic interventions.

Arginine Decarboxylase Is Essential for Pneumococcal Stress Responses.

Polyamines such as putrescine, cadaverine, and spermidine are small cationic molecules that play significant roles in cellular processes, including bacterial stress responses and host-pathogen interactions. Streptococcus pneumoniae is an opportunistic human pathogen, which causes several diseases that account for significant morbidity and mortality worldwide. As it transits through different host niches, S. pneumoniae is exposed to and must adapt to different types of stress in the host microenvironment. We earlier reported that S. pneumoniae TIGR4, which harbors an isogenic deletion of an arginine decarboxylase (ΔspeA), an enzyme that catalyzes the synthesis of agmatine in the polyamine synthesis pathway, has a reduced capsule. Here, we report the impact of arginine decarboxylase deletion on pneumococcal stress responses. Our results show that ΔspeA is more susceptible to oxidative, nitrosative, and acid stress compared to the wild-type strain. Gene expression analysis by qRT-PCR indicates that thiol peroxidase, a scavenger of reactive oxygen species and aguA from the arginine deiminase system, could be important for peroxide stress responses in a polyamine-dependent manner. Our results also show that speA is essential for endogenous hydrogen peroxide and glutathione production in S. pneumoniae. Taken together, our findings demonstrate the critical role of arginine decarboxylase in pneumococcal stress responses that could impact adaptation and survival in the host.

SP_0916 Is an Arginine Decarboxylase That Catalyzes the Synthesis of Agmatine, Which Is Critical for Capsule Biosynthesis in Streptococcus pneumoniae.

The global burden of invasive pneumococcal diseases, including pneumonia and sepsis, caused by Streptococcus pneumoniae, a Gram-positive bacterial pathogen, remains a major global health risk. The success of pneumococcus as a pathogen can be attributed to its ability to regulate the synthesis of capsular polysaccharide (CPS) during invasive disease. We previously reported that deletion of a putative lysine decarboxylase (LDC; ΔSP_0916) in pneumococcal serotype 4 (TIGR4) results in reduced CPS. SP_0916 locus is annotated as either an arginine or a LDC in pneumococcal genomes. In this study, by biochemical characterization of the recombinant SP_0916, we determined the substrate specificity of SP_0916 and show that it is an arginine decarboxylase (speA/ADC). We also show that deletion of the polyamine transporter (potABCD) predicted to import putrescine and spermidine results in reduced CPS, while deletion of spermidine synthase (speE) for the conversion of putrescine to spermidine had no impact on the capsule. Targeted metabolomics identified a correlation between reduced levels of agmatine and loss of capsule in ΔspeA and ΔpotABCD, while agmatine levels were comparable between the encapsulated TIGR4 and ΔspeE. Exogenous supplementation of agmatine restored CPS in both ΔpotABCD and ΔspeA. These results demonstrate that agmatine is critical for regulating the CPS, a predominant virulence factor in pneumococci.

Polyamine Synthesis Effects Capsule Expression by Reduction of Precursors in Streptococcus pneumoniae.

Streptococcus pneumoniae (pneumococcus, Spn) colonizes the human nasopharynx asymptomatically but can cause infections such as otitis media, and invasive pneumococcal disease such as community-acquired pneumonia, meningitis, and sepsis. Although the success of Spn as a pathogen can be attributed to its ability to synthesize and regulate capsular polysaccharide (CPS) for survival in the host, the mechanisms of CPS regulation are not well-described. Recent studies from our lab demonstrate that deletion of a putative polyamine biosynthesis gene (ΔcadA) in Spn TIGR4 results in the loss of the capsule. In this study, we characterized the transcriptome and metabolome of ΔcadA and identified specific mechanisms that could explain the regulatory role of polyamines in pneumococcal CPS biosynthesis. Our data indicate that impaired polyamine synthesis impacts galactose to glucose interconversion via the Leloir pathway which limits the availability of UDP-galactose, a precursor of serotype 4 CPS, and UDP-N-acetylglucosamine (UDP-GlcNAc), a nucleotide sugar precursor that is at the intersection of CPS and peptidoglycan repeat unit biosynthesis. Reduced carbon flux through glycolysis, coupled with altered fate of glycolytic intermediates further supports impaired synthesis of UDP-GlcNAc. A significant increase in the expression of transketolases indicates a potential shift in carbon flow toward the pentose phosphate pathway (PPP). Higher PPP activity could constitute oxidative stress responses in ΔcadA which warrants further investigation. The results from this study clearly demonstrate the potential of polyamine synthesis, targeted for cancer therapy in human medicine, for the development of novel prophylactic and therapeutic strategies for treating bacterial infections.

The Role of Cadaverine Synthesis on Pneumococcal Capsule and Protein Expression.

Invasive infections caused by Streptococcus pneumoniae, a commensal in the nasopharynx, pose significant risk to human health. Limited serotype coverage by the available polysaccharide-based conjugate vaccines coupled with increasing incidence of antibiotic resistance complicates therapeutic strategies. Bacterial physiology and metabolism that allows pathogens to adapt to the host are a promising avenue for the discovery of novel therapeutics. Intracellular polyamine concentrations are tightly regulated by biosynthesis, transport and degradation. We previously reported that deletion of cadA, a gene that encodes for lysine decarboxylase, an enzyme that catalyzes cadaverine synthesis results in an attenuated phenotype. Here, we report the impact of cadA deletion on pneumococcal capsule and protein expression. Our data show that genes for polyamine biosynthesis and transport are downregulated in ∆cadA. Immunoblot assays show reduced capsule in ∆cadA. Reduced capsule synthesis could be due to reduced transcription and availability of precursors for synthesis. The capsule is the predominant virulence factor in pneumococci and is critical for evading opsonophagocytosis and its loss in ∆cadA could explain the reported attenuation in vivo. Results from this study show that capsule synthesis in pneumococci is regulated by polyamine metabolism, which can be targeted for developing novel therapies.