The Host-Microbiome Response to Hyperbaric Oxygen Therapy in Ulcerative Colitis Patients

BACKGROUND & AIMS

Hyperbaric oxygen therapy (HBOT) is a promising treatment for moderate-to-severe ulcerative colitis. However, our current understanding of the host and microbial response to HBOT remains unclear. This study examined the molecular mechanisms underpinning HBOT using a multi-omic strategy.

METHODS

Pre- and post-intervention mucosal biopsies, tissue, and fecal samples were collected from HBOT phase 2 clinical trials. Biopsies and fecal samples were subjected to shotgun metaproteomics, metabolomics, 16s rRNA sequencing, and metagenomics. Tissue was subjected to bulk RNA sequencing and digital spatial profiling (DSP) for single-cell RNA and protein analysis, and immunohistochemistry was performed. Fecal samples were also used for colonization experiments in IL10-/- germ-free UC mouse models.

RESULTS

Proteomics identified negative associations between HBOT response and neutrophil azurophilic granule abundance. DSP identified an HBOT-specific reduction of neutrophil STAT3, which was confirmed by immunohistochemistry. HBOT decreased microbial diversity with a proportional increase in Firmicutes and a secondary bile acid lithocholic acid. A major source of the reduction in diversity was the loss of mucus-adherent taxa, resulting in increased MUC2 levels post-HBOT. Targeted database searching revealed strain-level associations between Akkermansia muciniphila and HBOT response status. Colonization of IL10-/- with stool obtained from HBOT responders resulted in lower colitis activity compared with non-responders, with no differences in STAT3 expression, suggesting complementary but independent host and microbial responses.

CONCLUSIONS

HBOT reduces host neutrophil STAT3 and azurophilic granule activity in UC patients and changes in microbial composition and metabolism in ways that improve colitis activity. Intestinal microbiota, especially strain level variations in A muciniphila, may contribute to HBOT non-response.

Abstract TMP1: Multi-omic Biomarker Development In A Mendelian Neurovascular Disease, Cavernous Angioma

Introduction: Cavernous Angioma (CA) is a hemorrhagic neurovascular disease characterized by either a familial form with autosomal dominant germline mutations in one of three CCM genes or a sporadic form with somatic mutations of the same genes. Circulating proteins have been previously investigated as possible diagnostic and prognostic biomarkers of disease activity, with up to 86% and 88% sensitivity and specificity, respectively. We hypothesize that differentially expressed (DE) plasma microRNAs and metabolites in CA patients can be integrated with plasma proteins to increase the sensitivity and specificity of circulating CA biomarkers.

Methods: Mechanistically relevant homologous DE miRNAs were identified between familial CA patients and preclinical murine models and validated in an independent cohort of patients using real time qPCR. In conjunction, DE metabolites were determined in CA patients using liquid-chromatography mass spectrometry. The interactions of these metabolites with the previously established CA transcriptome, proteome, and microbiome were queried to assess for mechanistic relevance. Optimal diagnostic models of proteins, DE miRNAs, and DE metabolites alone were next established. Plasma metabolites and miRNAs were then separately integrated with protein, using a machine learning-implemented, Bayesian approach to develop diagnostic CA biomarkers.

Results: The optimal diagnostic biomarker model with only DE miRNAs performed at up to 68%, while proteins and metabolites achieved up to 68%, and 82% accuracy respectively. The optimal combination for proteins with miRNAs improved the diagnostic association of familial-CA disease to up to 94.7% sensitivity and 100% specificity. Integrating metabolites and proteins improved the diagnosis of CA disease and its clinical manifestations to 100% sensitivity and 100% specificity.

Conclusion: Combining plasma proteins with miRNAs or metabolites can improve diagnostic accuracy of CA disease and its disease characteristics above any single molecular modality alone. Future studies should incorporate proteins, miRNAs, and metabolites to further increase diagnostic accuracy, and validate these in a larger cohort with control for demographic and disease features.

Direct Detection of Beta-Lactamase Mediated Antibiotic Resistance In Clinical Specimens

Antibiotic resistance mediated by beta-lactamase enzyme expression is a serious and growing threat. The typical workflow in a clinical microbiology lab leading to identification of beta-lactamase expressing organisms typically requires 48 to 72 hours and involves multiple manual steps. Empiric treatment with potentially ineffective antibiotics often occurs before susceptibility testing results are available. Objective: The objective of our study was to determine if beta-lactamase activity could be detected in clinical urine samples to provide same-day rule-out of select empiric treatment regimens for urinary tract infections. Methods: We acquired urine samples from 40 patients with extended spectrum beta-lactamase expressing (ESBL) infections and 100 patients without ESBL infection as determined by standard culture and sensitivity methods. These samples were incubated with spiked beta-lactam antibiotics susceptible to ESBL degradation (ceftriaxone, cefazolin, and oxacillin) or resistant to ESBL degradation (meropenem). Results: Hydrolysis of spiked drug was detected after a 4 hour incubation with either liquid-chromatography mass-spectrometry (LC-MS) or matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) methods. A 100 to 1000 fold reductions in measured concentrations of spiked ceftriaxone, cefazolin, or oxacillin were observed with LC-MS or MALDI-TOF methods for all 40 ESBL containing specimens and unchanged concentrations of spiked drug were observed in all 100 non-ESBL containing specimens. Concentration of spiked meropenem (resistant to ESBL degradation) were unchanged in all specimens after incubation regardless of ESBL status. Addition of a beta-lactamase inhibitor prevented ESBL degradation of ceftriaxone, cefazolin, and oxacillin demonstrating that beta-lactamase activity (and not another method of drug degradation or signal masking) is being detected. Incubation times as long as 24 hours (to determine method specificity) and as short as 30 minutes (to determine method sensitivity) all showed robust discrimination between ESBL-containing and non-ESBL containing specimens. Conclusion: Our results demonstrate that beta-lactamase activity can be robustly detected in urine samples days before culture and susceptibility results could be available. Clinical utilization of the assay described would enable clinicians to reduce ineffective empiric treatment of ESBL urinary infections.

130 Individual Differences in Skin Temperature Responses to Cold Pressor Stress During Sleep Restriction and Circadian Misalignment

Introduction

Individual differences in cognition during sleep restriction and circadian misalignment have been shown to be trait-like. Here we explored the consistency of individual differences in cardiovascular responses to the cold pressor test (CPT) measured by changes in the distal-proximal skin temperature gradient (DPG) using the contralateral hand to that immersed in the ice water bath, which reflects a reflex cutaneous vasoconstriction.

Methods

Eighteen healthy participants (8 females) mean (±SD) age 25.28 (±4.3), underwent two identical in-laboratory combined sleep restriction and circadian misalignment protocols preceded by an 8h baseline in-laboratory sleep opportunity. The participants were given a 3h sleep opportunity on night 2 and a 3h sleep opportunity on days 3 and 4 followed by recovery sleep. The CPT occurred the morning after the baseline sleep opportunity and the morning before recovery sleep. Participants maintained a seated posture beginning 30 min prior to the CPT and skin temperature was assessed starting 15 min before until 45 min after the CPT. DPG (proximal=subclavicular; distal=hand palmar) data were averaged into 3 min bins. Changes in DPG from pre-CPT and 5 min post-CPT were assessed as the primary outcome using mixed-model ANOVAs. Intra-class correlation coefficients (ICC) were calculated to measure consistency of individual differences for DPG responses.

Results

Mixed-model ANOVA revealed significant effects of time and combined sleep restriction and circadian misalignment on DPG during the CPT (both p<0.05), such that the DPG was wider (i.e., more negative) post-CPT and during sleep restriction and circadian misalignment. Participants showed moderately consistent DPG responses across visits 1 and 2 at baseline (ICC=0.59) and substantially consistent DPG responses during sleep restriction and circadian misalignment (ICC=0.67). Further, participants showed moderately consistent DPG responses when comparing changes between baseline and sleep restriction and circadian misalignment across visits (ICC=0.58).

Conclusion

Findings support that combined sleep restriction and circadian misalignment is associated with sympathetic activation and that individual differences in the DPG response to cold pressor stress are consistent.

Support (if any)

Office of Naval Research MURI grant N00014-15-1-2809, NIH/NCATS Colorado CTSA Grant UL1TR002535

114 Stability of Gut Microbiome Alpha Diversity During Combined Sleep Restriction and Circadian Misalignment

Introduction

Disturbed gut microbiome diversity has been associated with poor health outcomes and various disease states. We investigated the impact of combined sleep restriction (3h time in bed [TIB] sleep opportunities per day) and circadian misalignment (daytime sleep and nighttime wakefulness) on gut microbiome alpha diversity in healthy young individuals in a controlled laboratory setting.

Methods

Twenty healthy adults (8 female), mean age (±SD) 25.65(±4.2) completed a 39-day protocol consisting of two laboratory visits lasting 4 days each. Two weeks of ambulatory monitoring prior to laboratory visits confirmed ~8h habitual sleep duration per night. Participants consumed energy-balanced diets, identical within participants, 2 days before and during the laboratory visits. The laboratory visits consisted of sleep opportunities as follows: night 1 (8h TIB), night 2 (3h TIB), day 3 (3h TIB) and day 4 (3h TIB). Fecal microbiome samples were obtained at baseline between day 1 and 2, and during sleep and circadian disruption (between day 3 and 4). Alpha diversity measures were calculated using Pielou’s evenness, Faith’s phylogenetic diversity and number of observed OTUs.

Results

Linear mixed models with subject as a random factor and visit as a fixed factor were performed to assess whether any alpha diversity measures changed during sleep and circadian disruption compared to baseline. Alpha diversity did not change significantly between baseline and sleep and circadian disruption (all p > 0.57). Additionally, intraclass correlation coefficients (ICCs) were calculated at baseline and during sleep and circadian disruption to determine if alpha diversity measures showed trait-like stability at both time points. ICCs were substantial to almost perfect (ICC 0.64–0.84) at baseline and substantial (ICC 0.70–0.80) during sleep and circadian disruption.

Conclusion

Four days of combined sleep restriction and circadian misalignment does not appear to alter alpha diversity of gut microbiota species in healthy adults. Further, substantial to almost perfect intraclass correlation coefficients suggest alpha diversity of the human microbiome is stable during combined sleep and circadian perturbation and that examination at the level of microbiota community composition and functional outcomes are needed.

Support (if any)

Office of Naval Research MURI (N00014- 15-1-2809), NIH/NCATS (UL1TR002535), NIH T32 HL149646, CU Undergraduate Research Opportunities.

Molecular Networking: A Useful Tool for the Identification of New Psychoactive Substances in Seizures by LC-HRMS

New Psychoactive Substances (NPS) are a global concern since they are spreading at an unprecedented rate. Despite their commerce still being limited compared to traditional illicit drugs, the identification of NPS in seizures may represent a challenge because of the variety of possible structures. In this study we report the successful application of molecular networking (MN) to identify unexpected fentanyl analogs in two seizures. The samples were extracted with 1 mL of methanol and analyzed with an untargeted data-dependent acquisition approach by LC–HRMS. The obtained data were examined using the MN workflow within the Global Natural Product Search (GNPS). A job was submitted to GNPS by including both seizures and standard mixtures containing synthetic cannabinoids and fentanyls raw files; spectra obtained from standards were used to establish representative networks for both molecular classes. All synthetic cannabinoids in the mixture were linked together resulting in a molecular network despite their different fragmentation spectra. Looking at fentanyls, all the molecules with the typical 188.143 and 105.070 fragments were combined in a representative network. By exploiting the standard networks two unexpected fentanyls were found in the analyzed seizures and were putatively annotated as para-fluorofuranylfentanyl and (iso)butyrylfentanyl. The identity of these two fentanyl analogs was confirmed by NMR analysis. Other m/z ratios in the seizures were compatible with fentanyl derivatives; however, they appeared to be minor constituents, probably impurities or synthetic byproducts. The latter might be of interest for investigations of common fingerprints among different seizures.

Consumption of Fermented Plant Foods Is Associated with Systematic Differences in the Human Gut Microbiome and Metabolome

Objectives

Fermented foods have gained much attention due to their proposed gut health benefits from recent clinical trials. However, very few studies have explored the effects of fermented foods, especially of plant origin, on gut microbiota composition and functional capacity in large human cohorts. Thus, the objective of this study was to assess whether self-reported fermented plant food consumption is associated with compositional or functional microbiome changes in a subset of individuals in the American Gut Project (AGP) cohort.

Methods

Using a multi-omics approach (e.g., 16S rRNA amplicon sequencing, metagenomic sequencing, and untargeted mass spectrometry), we analyzed stool samples from 6811 healthy individuals from the AGP including 115 individuals specifically recruited for their fermented plant food consumption for a targeted four-week longitudinal study.

Results

We observed subtle, yet statistically significant differences between fermented plant food consumers and non-consumers in beta diversity as well as differential taxa between the two groups. We found that the metabolome of fermented plant food consumers was enriched with conjugated linoleic acid (CLA), a putatively health-promoting compound. Cross-omic analyses between metagenomic sequencing and mass spectrometry suggest that CLA may be driven by taxa associated with fermented plant food consumers.

Conclusions

Collectively, we found modest, yet persistent signatures associated with fermented plant food consumption that appear present in multiple omic types, which motivates further investigation of how different types of fermented foods may impact the human gut microbiome and overall health.

Funding Sources

Danone Nutricia Research.

Detection of Natural Products and Their Producers in Ocean Sediments

Thousands of natural products have been identified from cultured microorganisms, yet evidence of their production in the environment has proven elusive. Technological advances in mass spectrometry, combined with public databases, now make it possible to address this disparity by detecting compounds directly from environmental samples. Here, we used adsorbent resins, tandem mass spectrometry, and next-generation sequencing to assess the metabolome of marine sediments and its relationship to bacterial community structure. We identified natural products previously reported from cultured bacteria, providing evidence they are produced in situ, and compounds of anthropogenic origin, suggesting this approach can be used as an indicator of environmental impact. The bacterial metabolite staurosporine was quantified and shown to reach physiologically relevant concentrations, indicating that it may influence sediment community structure. Staurosporine concentrations were correlated with the relative abundance of the staurosporine-producing bacterial genus Salinispora and production confirmed in strains cultured from the same location, providing a link between compound and candidate producer. Metagenomic analyses revealed numerous biosynthetic gene clusters related to indolocarbazole biosynthesis, providing evidence for noncanonical sources of staurosporine and a path forward to assess the relationships between natural products and the organisms that produce them. Untargeted environmental metabolomics circumvents the need for laboratory cultivation and represents a promising approach to understanding the functional roles of natural products in shaping microbial community structure in marine sediments.IMPORTANCE Natural products are readily isolated from cultured bacteria and exploited for useful purposes, including drug discovery. However, these compounds are rarely detected in the environments from which the bacteria are obtained, thus limiting our understanding of their ecological significance. Here, we used environmental metabolomics to directly assess chemical diversity in marine sediments. We identified numerous metabolites and, in one case, isolated strains of bacteria capable of producing one of the compounds detected. Coupling environmental metabolomics with community and metagenomic analyses provides opportunities to link compounds and producers and begin to assess the complex interactions mediated by specialized metabolites in marine sediments.

Predicting proteome allocation, overflow metabolism, and metal requirements in a model acetogen

The unique capability of acetogens to ferment a broad range of substrates renders them ideal candidates for the biotechnological production of commodity chemicals. In particular the ability to grow with H₂:CO₂ or syngas (a mixture of H₂/CO/CO₂) makes these microorganisms ideal chassis for sustainable bioproduction. However, advanced design strategies for acetogens are currently hampered by incomplete knowledge about their physiology and our inability to accurately predict phenotypes. Here we describe the reconstruction of a novel genome-scale model of metabolism and macromolecular synthesis (ME-model) to gain new insights into the biology of the model acetogen Clostridium ljungdahlii. The model represents the first ME-model of a Gram-positive bacterium and captures all major central metabolic, amino acid, nucleotide, lipid, major cofactors, and vitamin synthesis pathways as well as pathways to synthesis RNA and protein molecules necessary to catalyze these reactions, thus significantly broadens the scope and predictability. Use of the model revealed how protein allocation and media composition influence metabolic pathways and energy conservation in acetogens and accurately predicted secretion of multiple fermentation products. Predicting overflow metabolism is of particular interest since it enables new design strategies, e.g. the formation of glycerol, a novel product for C. ljungdahlii, thus broadening the metabolic capability for this model microbe. Furthermore, prediction and experimental validation of changing secretion rates based on different metal availability opens the window into fermentation optimization and provides new knowledge about the proteome utilization and carbon flux in acetogens.

Acetogens are renowned for their potential biotechnological applications. The model acetogen Clostridium ljungdahlii has been studied intensively for its ability to produce biofuels from sustainable resources, like syngas. We describe a novel genome-scale model of metabolism and gene expression (ME-model) to gain insights into this model acetogen. This first ME-model for a Gram-positive bacterium contains all major metabolic and biosynthetic pathways and calculates accurate proteome allocations under diverse growth conditions, thereby significantly broadening the scope of predictability of metabolic models. Furthermore, the ME-model enables rational medium design for improved production. Our experimental validation implies wide applicability to others strains for rapid improvement of yield and titer in biotechnology-relevant applications.

Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians

Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.

Intermittent Hypoxia and Hypercapnia Accelerate Atherosclerosis, Partially via Trimethylamine-Oxide

Obstructive sleep apnea (OSA) is a common disorder characterized by intermittent hypoxia and hypercapnia (IHC) during sleep. OSA has been shown to be a risk factor for atherosclerosis, but the relation of IHC to the induction or progression of atherosclerosis is not well understood. To dissect the mechanisms involved, we compared atherosclerotic lesion formation in two mouse models, i.e., apolipoprotein E (ApoE) and low density lipoprotein receptor (Ldlr)-deficient mice, with or without IHC exposure. Ten-week-old ApoE-/- or Ldlr-/- mice were fed a high-fat diet for 4 or 8 weeks while being exposed to IHC for 10 hours/day or room air (RA) for 24 hours/day. En face lesions of the aorta, aortic arch, and pulmonary artery (PA) were examined. Moreover, 3,3-dimethyl-1-butanol (DMB), an inhibitor of microbial trimethylamine (TMA) production, was used to determine the contribution of TMA-oxide (TMAO) to IHC-induced atherosclerosis. Eight weeks of IHC exposure expedited the formation of atherosclerosis in both the PA and aortic arch of ApoE-/- mice, but only in the PA of Ldlr-/- mice (ApoE-/- PA 8 wk, IHC 35.4 ± 1.9% versus RA 8.0 ± 2.8%, P < 0.01). The atherosclerotic lesions evolved faster and to a more severe extent in ApoE-/- mice as compared with Ldlr-/- mice (PA IHC 8 wk, ApoE-/- 35.4 ± 1.9% versus Ldlr-/- 8.2 ± 1.5%, P < 0.01). DMB significantly attenuated but did not totally eliminate IHC-induced PA atherosclerosis. Our findings suggest that IHC, a hallmark of OSA, accelerates the progression of atherosclerosis in the aorta and especially in the PA. This process is partly inhibited by DMB, demonstrating that microbial metabolites may serve as therapeutic targets for OSA-induced atherosclerosis.

An Elegan(t) Screen for Drug-Microbe Interactions

Microbes affect drug responses, but mechanisms remain elusive. Two papers in Cell exploit C. elegans to infer anticancer drug mechanisms. Through high-throughput screens of drug-microbe-host interactions, García-González et al. (2017) and Scott et al. (2017) determine that bacterial metabolism underpins fluoropyrimidine cytotoxicity, providing a paradigm for unraveling bacterial mechanisms in drug metabolism.

Microbiome Tools for Forensic Science

Microbes are present at every crime scene and have been used as physical evidence for over a century. Advances in DNA sequencing and computational approaches have led to recent breakthroughs in the use of microbiome approaches for forensic science, particularly in the areas of estimating postmortem intervals (PMIs), locating clandestine graves, and obtaining soil and skin trace evidence. Low-cost, high-throughput technologies allow us to accumulate molecular data quickly and to apply sophisticated machine-learning algorithms, building generalizable predictive models that will be useful in the criminal justice system. In particular, integrating microbiome and metabolomic data has excellent potential to advance microbial forensics.

Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease

Background. Cystic fibrosis (CF) is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE) that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy.

Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples) to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data was analyzed with MS/MS molecular networking and multivariate statistics.

Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable). Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF) and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events) as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes.

Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

Molecular and chemical dialogues in bacteria-protozoa interactions

Protozoan predation of bacteria can significantly affect soil microbial community composition and ecosystem functioning. Bacteria possess diverse defense strategies to resist or evade protozoan predation. For soil-dwelling Pseudomonas species, several secondary metabolites were proposed to provide protection against different protozoan genera. By combining whole-genome transcriptome analyses with (live) imaging mass spectrometry (IMS), we observed multiple changes in the molecular and chemical dialogues between Pseudomonas fluorescens and the protist Naegleria americana. Lipopeptide (LP) biosynthesis was induced in Pseudomonas upon protozoan grazing and LP accumulation transitioned from homogeneous distributions across bacterial colonies to site-specific accumulation at the bacteria-protist interface. Also putrescine biosynthesis was upregulated in P. fluorescens upon predation. We demonstrated that putrescine induces protozoan trophozoite encystment and adversely affects cyst viability. This multifaceted study provides new insights in common and strain-specific responses in bacteria-protozoa interactions, including responses that contribute to bacterial survival in highly competitive soil and rhizosphere environments.

Oxidative cascades: a facile biosynthetic strategy for the assembly of complex molecules

Electron-rich aromatic compounds undergo a facile tandem reaction sequence involving an iterative two-electron oxidation/aromatization. This review will describe the application of this motif to the synthesis of dimethylbenzimidazole, pyoverdine, actinomycin, cystodytin, pyrroloquinoline quinone, and the cataract pigment.

Aerobic tryptophan degradation pathway in bacteria: novel kynurenine formamidase

While a variety of chemical transformations related to the aerobic degradation of L-tryptophan (kynurenine pathway), and most of the genes and corresponding enzymes involved therein have been predominantly characterized in eukaryotes, relatively little was known about this pathway in bacteria. Using genome comparative analysis techniques we have predicted the existence of the three-step pathway of aerobic L-tryptophan degradation to anthranilate (anthranilate pathway) in several bacteria. Based on the chromosomal gene clustering analysis, we have identified a previously unknown gene encoding for kynurenine formamidase (EC 3.5.1.19) involved with the second step of the anthranilate pathway. This functional prediction was experimentally verified by cloning, expression and enzymatic characterization of recombinant kynurenine formamidase orthologs from Bacillus cereus, Pseudomonas aeruginosa and Ralstonia metallidurans. Experimental verification of the inferred anthranilate pathway was achieved by functional expression in Escherichia coli of the R. metallidurans putative kynBAU operon encoding three required enzymes: tryptophan 2,3-dioxygenase (gene kynA), kynurenine formamidase (gene kynB), and kynureninase (gene kynU). Our data provide the first experimental evidence of the connection between these genes (only one of which, kynU, was previously characterized) and L-tryptophan aerobic degradation pathway in bacteria.

The biosynthesis of nicotinamide adenine dinucleotides in bacteria

The nicotinamide adenine dinucleotides (NAD, NADH, NADP, and NADPH) are essential cofactors in all living systems and function as hydride acceptors (NAD, NADP) and hydride donors (NADH, NADPH) in biochemical redox reactions. The six-step bacterial biosynthetic pathway begins with the oxidation of aspartate to iminosuccinic acid, which is then condensed with dihydroxyacetone phosphate to give quinolinic acid. Phosphoribosylation and decarboxylation of quinolinic acid gives nicotinic acid mononucleotide. Adenylation of this mononucleotide followed by amide formation completes the biosynthesis of NAD. An additional phosphorylation gives NADP. This review focuses on the mechanistic enzymology of this pathway in bacteria.